Publications

The energy transition requires rethinking how we produce and consume energy. Energy communities (EC) provide a recent legal framework for sharing energy, aiming to reduce energy bills and the environmental footprint of their participants. One of the challenges is adapting economic models to this technological upheaval. In this context, cooperative games, based on game theory, are valuable tools for modeling energy management through cooperation. However, despite their promising characteristics, cooperative games are limited by their computational complexity. The required computation time to solve cooperative games increases exponentially with the number of participants, restricting their application in energy management. This paper aims to propose a solution to apply cooperative game theory tools to larger communities using a multidisciplinary approach. For this purpose, a game subdivision approach based on the specific properties of energy communities is proposed. This methodology will be shown to be efficient in terms of computation time. While the game theory concepts are depreciated by limiting computing time, the sub-games method can become an interesting tool in energy management. Advantages and drawbacks in terms of energy management and game theory are discussed in this paper.

In order to maintain grid-forming converter (GFM) voltage source behaviour under current limiting mode, a threshold virtual impedance (TVI) current limiting control is proposed, which is controlled in the positive and negative sequence synchronous reference frames for symmetrical and asymmetrical fault conditions. The converter current is strictly limited within the maximum limit without the need for current saturation limiters. Since the TVI control is based on 3-phase sinusoidal currents, it is shown that using the measured current instead of the existing current reference for the TVI control may cause oscillatory behaviour when a large switching delay is considered. Since sequence extraction control is necessary, the paper also compares GFM dynamic stability under the three well-known sequence extraction methods (i.e. delay cancellation, dual second order generalized integrator, and decoupled double synchronous reference frame). It is shown that the differences are small when GFM is not in current limiting mode, but they are large when GFM is in current limiting mode or switching delays are considered.

The energy sources in a Hybrid Energy Storage System are coupled by a DC–DC converter. Nevertheless, this device’s mass is irrelevant when evaluating the performance of such a system in terms of density, so it must be reduced to achieve maximum performance. This can be achieved with the solution presented in this paper: a coupling architecture based on a controlled current source, in which the DC–DC converter’s processed power depends on the voltage difference between the two sources. If this difference is zero, so is the power processed by the converter. Minimizing this power leads to a reduction of the converter’s mass and volume, increasing system performance. In this paper, the controlled current source cascade architecture combines two lithium-ion batteries to supply a limited-range electric vehicle. Its operation is addressed and validated by simulation and experimental results. For the experimental validation, the batteries and the load were emulated by power supplies, with a 2 kg, 3.3 kW evaluation board serving as DC–DC converter. The findings reveal that the examined architecture enables a substantial reduction in the converter’s sizing power, up to a factor of 14 compared to a conventional solution commonly seen in the literature.

Bifacial photovoltaic (PV) modules, capable of capturing solar energy from both sides of the cells, are becoming increasingly popular as their manufacturing costs approach those of traditional monofacial modules. Accurate estimation of their power generation capacity is essential for optimizing their use. This study evaluates a power production model for bifacial PV modules using local irradiance data from Razon+ in Sherbrooke, Canada, and Solcast irradiance data derived from satellite imagery and weather models. The model's performance was assessed throughout the year, with particular attention to the impact of snow coverage during winter. To address computational efficiency, the study evaluated ray tracing and a 2D view factor model, selecting the more time-efficient method. Experimental validation showed that, using local irradiance data, the model achieved Normalized Root Mean Square Errors (NRMSE) of 18.77%, 4.94%, 3.93%, and 6.22% for winter, spring, summer, and fall, respectively. With Solcast data, the NRMSEs were 22.76%, 15.32%, 14.72%, and 17.78% for the corresponding seasons. While the model performed satisfactorily in spring, summer, and fall, it was less accurate in winter. To enhance winter accuracy, the model incorporated snow coverage, using snow depth as a metric to detect snow on the front surface. This adjustment improved the accuracy by 51.1%.

Key words: Photovoltaic / bifacial PV panels / power model / raytracing technique / view factor approach / snow losses

Grain-oriented electrical steels (GOES) are widely used in the manufacturing of high efficiency energy conversion systems thanks to their excellent magnetic properties along the rolling direction. Nevertheless, on the one hand, GOES exhibit strong magnetic anisotropy, resulting in distinct magnetic properties regarding the direction of the applied magnetic field to the rolling direction. On the other hand, GOES undergoes changes in their magnetic properties due to the industrial manufacturing process and mechanical constraints during operation. In general, stress, and particularly compressive stress, deteriorates magnetic properties. This paper deals with the modeling of the magnetic behavior of GOES under compressive stress. The orientation distribution function (ODF) based approach recently applied to describe the B-H first magnetization curves of a conventional GOES without stress as well as under applied uniaxial mechanical tensile stress is extended to account for the effect of compressive stress, with different considerations of modeling. The magnetic properties and the sensitivity of the ODF-based model to the magnetization direction as well as to the applied compressive stress are analyzed. Oscillation issues inherent to the ODF-based model are also discussed.

The future multi-terminal direct-current (MTDC) grid will require the interconnection of point-to-point high-voltage (HV) DC links with different specifications such as DC voltage level, system grounding configuration and HVDC technology. To adapt these differences, it is obligatory for DC/DC converters to interconnect HVDC links. Additionally, they are capable of providing supplementary functionalities as they are highly controllable devices. In this article, a primary virtual resistance DC voltage controller associated with DC/DC converter is proposed for managing DC grid voltages of the interconnected HVDC grids, increasing the reliability of the system. The commonly known topology, Front-to-Front Modular Multilevel Converter (F2F-MMC) is adopted for DC/DC converter. Time-domain simulations are performed using EMTP software for validating the
controller behaviour under power disturbances and large events of loss of one converter in a MMC-based MTDC system. The converters are modelled using reduced order modelling (ROM) methodology. Apart from this, dynamic studies have been carried out using a linear state space model for small-signal stability analysis of a HVDC system integrating DC/DC
converter with a virtual resistance DC voltage controller. The results are examined through parametric sensitivity analysis.

With the increasing penetration of power electronic converters in the power system induced by the energy transition, Grid Forming (GFM) technology emerges as crucial for complementing traditional synchronous generators in fulfilling system needs. All over the world, TSOs have started introducing performance-based requirements to define the desired behaviour of GFM units without prescribing specific technical solutions. Based on these specifications, manufacturers design their grid-connected equipment. However, depending on requirements, challenges may arise in optimizing control strategies without hardware modifications, potentially becoming cost-driving factors. Intellectual property protection limits information disclosure, restricting the guidance available to TSOs during cost–benefit assessments. Academic contributions on GFM control and generic models can bridge the gap, providing a fair portrayal of the general behaviour and then facilitates an open discussion on their ability to meet the requirements and contribute to fulfil system needs. This survey paper provides a comprehensive overview of the perspectives offered by these diverse stakeholders.

With the integration of power electronic converters and components, an accurate thermal design becomes essential. Hence, precise thermal models for components are needed for their optimal design. This paper focuses on the development of an analytical model for the design of thermal resistance of planar magnetic cores (PMC). Based on computational fluid dynamic (CFD) simulations, the PMC design thermal resistance variation is studied, according to ambient temperature and level of losses. Then, a polynomial equation is developed to model those variations, and coefficients are deduced for all the sizes of PMC. This analytical model, useful for designers, is finally validated with thermal measurements on a planar transformer prototype.

Schottky-type p-GaN gate Gallium Nitride High Electron Mobility Transistors (GaN-HEMTs) suffer from threshold voltage ( Vth ) instability phenomenon. Both positive and negative Vth shifts are reported when device undertakes the voltage bias, but the impact of this Vth instability phenomenon on device switching behaviors is less investigated. In this study, the drain-source voltage ( Vds ) induced bidirectional Vth shift in hard-switching condition is characterized and decoupled by an H-bridge based double-pulse test (DPT). Subsequently, the influence of Vth shift on switching behaviors is theoretically analyzed and demonstrated through SPICE simulation and experiment, showing how a positive shifted Vth can reduce the device turn-on commutation speed and increase the switching losses, and vice versa. The results suggest that the Vth instability phenomenon should be considered in accurate switching modeling.

Climate change is requiring changes in energy use. The integration of renewable energy sources
into the energy mix is a viable solution for electricity generation, but their intermittence forces
us to imagine new ways to consume and distribute electricity. Thus, new economic models and
new organizations have to be established. Energy communities are a recent legal solution to
share renewable energy among local actors. These structures facilitate the set-up of collective
self-consumption operations. Collective self-consumption is an interesting tool to increase local
renewable energy consumption and limit energy losses on the distribution grid. Consequently,
energy communities are pursuing a dual objective: reducing energy bills and the environmental
footprint of the participants. However, the distribution of gains generated through collective
self-consumption is one of the main obstacles to the implementation of energy communities. An
interesting possibility comes from game theory, especially from cooperative games, as solutions
concepts already exist to solve this kind of problem.
In this paper, a payoff distribution is proposed through a collaborative game. The aim of
the study is to explore ways to distribute gains generated by collective self consumptions on
individual self consumptions. These gains are 8% on the total energy bill and 25% on the
self-consumption rate, assuming a collective objective based on the self-consumption rate and
individual objectives based on the price of energy. In order to distribute the financial gains,
two major concepts in cooperative game theory are studied in this paper: the Shapley Value
and the Nucleolus. The advantages and drawbacks of these concepts in an energy community
context are identified, as these concepts are based on two different philosophies: The properties
of individual fairness of the Shapley Value and collective fairness of the Nucleolus for energy
management are therefore discussed. Furthermore, a methodology is proposed to enable a fairer
distribution of payoffs according to specific energy management parameters, such as efficiency
and flexibility.

This paper studies the influence of additional clutches on the fuel saving performance of a hybrid electric vehicle with a double-rotor electrical variable transmission. One clutch (C1) is introduced on the engine shaft to fix it to the ground, which enables two extra pure electric driving modes. The other (C2) is placed between the two rotors of the EVT to connect them together, resulting in the parallel hybrid and engine directly driving mode. To compare with the no-clutch EVT powertrain, a computationally efficient optimization framework, which combines dynamic programming and Pontryagin’s minimum principle, is employed to search the optimal fuel economy and mode controls under 15 various driving cycles. A bi-level formulation, containing a lower level that solves the underlying static optimization problems of components operation in combined driving modes and an upper level minimizes the Hamiltonian values, is incorporated into the optimization framework to further decrease the computation burden. The comparative analysis on three EVT powertrains, one without any clutches, one with two clutches and one with only C1, demonstrates that C1 could gain at most 5.66% of fuel saving under urban cycles, while the contribution of C2 is trivial to whichever driving conditions.

In this work, we propose an a posteriori goal-oriented error estimator for the harmonic A-Phi formulation arising in the modeling of eddy current problems, approximated by nonconforming finite element methods. It is based on the resolution of an adjoint problem associated with the initial one. For each of these two problems, a guaranteed equilibrated estimator is developed using some flux reconstructions. These fluxes also allow to obtain a goal-oriented error estimator that is fully computable and can be split in a principal part and a remainder one. Our theoretical results are illustrated by numerical experiments.

Grain-oriented electrical steels (GOES) are extensively utilized in power transformers to enhance energy efficiency and reduce their size and weight. GOES are characterized by their strong magnetic anisotropy, leading to distinct magnetic characteristics (behavior law and iron losses) according to the direction and the intensity of the applied field with respect to the rolling direction (RD). The Orientation Distribution Function (ODF) based approach is a convenient method for describing the anisotropy of the GOES behavior law owing to its ease of identification and implementation. However, it exhibits a significant oscillation issue at low magnetic fields. To address this issue, a high-order ODF-based method has been proposed in the literature. In this article, the ODF-based model, initially stress-free, is extended to include the effects of mechanical tensile stress on the first magnetization curves of a conventional GOES. An ODF-based model considering both magnetic anisotropy and mechanical tensile stress is then proposed. The results are discussed and compared with experimental data.

The interest of non-destructive testing (NDT) in steel material characterization is growing especially for quality and life cycle control. The Magnetic Barkhausen Noise (MBN) analysis shows an extreme sensitivity to different parameters: steel grade, grain size, microstructure, magnetic domains wall structure, residual stress, surface condition, etc. It is very difficult to distinguish the individual effect of each parameter on the steel MBN signature. This paper attempts to address this problematic by fixing most of these parameters and varying only one parameter of interest (either austenitizing or tempering temperature) to assess the ability of the MBN technique to dissociate the mechanical properties of different martensitic steel grades. The MBN technique presented herein has proven to be able to distinguish high-performance martensitic steel grades when applied according to the proposed experimental protocol.

This paper studies how the user charging practice affects battery degradation over time. To achieve this objective, a system oriented simplified aging model based on the literature is proposed. The differential calculation of the capacity loss is used for infinitesimal variations. The model inputs are the battery state of charge, the battery temperature and the cumulative number of full equivalent cycles. The output is the battery state of health. This model is identified and validated with experimental aging tests from the Renault Zoe 41kWh battery manufacturer. The battery model (electro-thermal and aging) interconnects with the vehicle traction model complete the system model. The battery electro-thermal and traction models are also validated with measurements on the studied vehicle. The Energetic Macroscopic Representation (EMR) formalism organizes in a unified way the interconnections of all the sub-system models. The impact of the charging interval and SoC on the battery aging is then studied. Five charging scenarios are studied by simulation while keeping the driving phases and the charging current the same. In these conditions, the average SoC is the main contributor for the battery aging. Compared to daily charge of the EV, a charge every 4 days extends the time to reach 80% of state of health by 36 % due to lower average SoC. The daily driving distance is fixed for every studied scenario.

In order to improve the driving performance of electric vehicles (EV), a permanent magnet synchronous motor with double V-shaped magnet structure (DVMPMSM) and its driving system are studied in this paper. A 150 kW DVMPMSM for EV is designed firstly, and the design parameters of the motor are determined. In order to overcome the drawbacks of the finite element analysis (FEA), especially the issue on calculating time, a dynamic equivalent magnetic network (EMN) model of the DVMPMSM is constructed, by which the air gap flux density, back electromotive force, electromagnetic torque and winding inductance parameters of the motor can be solved. Compared with the FEA, the dynamic EMN model constructed in this paper greatly increases the calculation speed while the calculation accuracy is maintained well. This paper also introduces the stator winding switching method to replace the field-weakening control method. Then, a vector control method of DVMPMSM based on dynamic EMN model and stator winding switching is proposed. The demands brought forward by EV for high torque output under low speed and high upper limit of speed can be well satisfied. Finally, the accuracy of the dynamic EMN model and the effectiveness of the proposed control method is validated through prototype experiments.

This paper analyzes the timetable impact on the energy consumption of a subway line. In most timetable studies, simplified models are used and can lead to misestimation of the braking energy and thus the energy transfer between braking vehicles and accelerating vehicles. In this paper, specific attention is paid to the models of the vehicles, the traction power substation, and the rail supply network to enable an accurate estimation of the energy consumption. The energetic macroscopic representation formalism is used to organize the models of the subsystems so they have the right interactions. The developed model is validated by experimental tests on a real subway line. The error on the global energy consumption is lower than 2.2%. The model is then employed to examine the influence of the vehicle time interval on energy consumption. A 10-second adjustment in this time interval can result in a substantial 22% decrease in energy consumption for the analyzed real subway line.

Optimal energy management for electrified vehicles can be achieved with a prior understanding of the velocity profile, whose prediction accuracy is influenced by the stochastic uncertainty of real driving cycles. This paper proposes a new state of charge planning method for plug-in hybrid electric trucks. The strategy eliminates the need for velocity prediction and relies solely on some readily available signals, such as estimated remaining distance and travel time. This exemption from velocity prediction avoids expensive computational costs, making it possible to use a more affordable processor. To test the strategy, four random driving cycles representing two different vocational uses are selected. The results show that the proposed strategy only increases fuel consumption by 1.3% for unknown urban and long-haul delivery cycles compared to the optimal strategy. Additionally, a sensitivity study reveals the robustness of the method on inaccurate navigation signals. These findings demonstrate that the proposed method is efficient and adaptive, making it suitable for existing truck applications without the need for additional hardware.

A Hybrid Energy Storage System (HESS) uses DC-DC converters to couple its energy sources. However, this device represents a "dead weight" in the system and must be reduced to a minimum in order to maximize the HESS' performance. This work proposes a new coupling architecture to reduce the converter's volume and mass. Not yet addressed in the literature, this architecture is based on a series coupling of the sources. In this case, a DC-DC converter is used to control the current difference between the two sources. If this difference is zero, so is the power processed by the converter. By reducing the power processed by the converter, its mass and volume can be reduced. Simulation and experimental tests were carried out to validate the architecture concept. For the latter, power supplies were used to emulate the batteries and the load, and a 2 kg, 3.3 kW evaluation board served as the DC-DC converter. The results show that, compared to a conventional solution that is usually adopted in the literature, with the series architecture, it is possible to reduce the converter sizing power by almost 3.7.

Grain-Oriented Electrical Steels (GOES) are widely used in transformers to increase energy efficiency while reducing the volume and weight of such transformers. These GOES are characterized by their strong anisotropy, which leads to different magnetic properties (behavior law and iron losses) depending on the strength and the direction of the applied magnetic field to the rolling direction (RD). To describe the anisotropy of the GOES behavior law, the Orientation Distribution Function (ODF) based approach shows interesting features regarding ease of identification and implementation. However, a significant oscillation issue in this model at low magnetic field exits. It is recently reported that a high-order ODF based method can improve the accuracy of the original model. But the high-order ODF based model implies an important number of experimental data according to different directions of the applied field to RD (different magnetization angles) to build a model with sufficient accuracy. In addition, the accuracy also depends on how the input magnetization angles are selected between the RD and the transverse direction (TD). In this article, an optimal algorithm for input magnetization angle selection is proposed for the high-order ODF based method. To validate the proposed algorithm, 13 magnetization angles have been measured. A comparative study has been conducted based on the original and the high-order ODF based models built with the proposed selected magnetization angles. It is shown that the proposed algorithm can reduce the number of experimental data needed for the ODF based model while providing an acceptable global error.

A nonreciprocal system composed of a one-dimensional piezoelectric phononic crystal whose periodic electrical conditions are modulated in time is presented. One-way longitudinal wave propagation is studied experimentally and compared to finite element temporal simulations. The modulation is performed by prescribing grounded or floating potential conditions on a periodic set of electrodes through external circuits. This approach makes it possible to consider a wide range of modulation speeds, and the large number of unit cells of the phononic crystal allows us to characterize experimentally the full dispersion curves of the system. This permits to observe the presence of directional bandgaps and to follow the shift in frequencies of these bandgaps as a function of the modulation speed. The experiments show the linear evolution of the central position of the bandgaps with the increase in the modulation speed, as well as their progressive closure, over a wide range of frequencies. Experiments are also used to estimate the evolution of bandgaps in a dispersive system, a problem discussed in several theoretical works but never observed experimentally. This work may constitute the foundation for experimental analysis of Floquet acoustic metamaterials, accelerated-modulation space-time metamaterials, or acoustic analog of the event horizon.

This study describes a systematic approach to generate control signals of a tactile simulator to render the touch of
textile fabrics. As a friction modulation tactile surface is used, control signals were generated from tribological
measurements on real surfaces. Forces were acquired from an artificial finger, with a texture mimicking fingerprints.
Then the signals are processed in frequency domain and send as control signal to the tactile stimulator.
This paper focusses on the potential benefits of including the fingerprint information in the simulation of fabrics
for achieving realistic tactile perception. A sensory analysis with 36 participants was carried out using the
generated control signals, and results show a better discrimination without fingerprint information.

This article discusses the use of simulation for analyzing the vibro-acoustic behavior of radial flux electrical machines under magnetic forces. Numerical simulation enables a systematic investigation of electromagnetic noise, vibration, and harshness (e-NVH) issues, but requires accurate modeling and this despite manufacturing uncertainties. Experimental validation is a necessary step to setup a multiphysics virtual prototyping e-NVH workflow. In particular, a key point is the magneto-mechanical coupling. In this study, the virtual work principle (VWP) is used for magnetic force calculation. The goal is to propose an accurate e-NVH model applied to a 12s10p radial flux electrical machine using a mesh-to-mesh projection. This e-NVH model enables to understand the origin of the noisiest orders along the whole speed range of the machine. Differences between simulation and experiments are discussed thanks to the modal participation factor of specific harmonics. Mesh-to-mesh projection results are compared to those obtained by using lumped tooth force, highlighting the contribution of the tooth tip moment to the vibration. Finally, the tooth modulation effect is discussed in the light of these results.

Decentralized energy production, particularly from photovoltaic (PV) systems, is becoming increasingly prevalent, leading to a rise in the number of energy producers and consumers, or ”prosumers”. These prosumers, equipped with their own energy generation and storage systems, are not just passive consumers but active participants in the energy market. They generate their own electricity, often from renewable sources, and can feed excess power back into the grid, store it for later use, or share it within a local energy community. This evolving energy paradigm presents new opportunities and challenges in terms of energy management and optimization, necessitating innovative approaches to ensure efficient and sustainable use of energy resources. This paper introduces an innovative storage management method for grid-connected photovoltaic (PV) systems. The method is designed to minimize either the economic or ecological cost, or to find an optimal balance between the two, under various tariff scenarios. This is achieved while adhering to a full self-consumption constraint imposed by the distribution system operator. The control strategy is underpinned by forecasts of electrical consumption, production, and CO2 emissions, which are developed using feedforward neural network models. These models are trained on data from a real-scale smart-grid demonstrator at the Catholic University of Lille, France. The results of the study offer a comparative analysis of the economic and ecological benefits of the three proposed strategies, demonstrating that the best compromise is achieved when considering the off-peak tariff option. Furthermore, a real-time controller was implemented on the Energy Management System (EMS) of the demonstrator and tested over a 24-hour period, yielding satisfactory results. This paper, therefore, presents a significant advancement in the field of storage management for grid-connected PV systems.

Texture, a fundamental object attribute, is perceived through multisensory information including touch and auditory cues. Coherent perceptions may rely on shared texture representations across different senses in the brain. To test this hypothesis, we delivered haptic textures coupled with a sound synthesizer to generate real-time textural sounds. Participants completed roughness estimation tasks with haptic, auditory, or bimodal cues in an MRI scanner. omatosensory, auditory, and visual cortices were all activated during haptic and auditory exploration, challenging the traditional view that primary sensory cortices are sense-specific. Furthermore, audio-tactile integration was found in secondary somatosensory (S2) and primary auditory cortices. Multivariate analyses revealed shared spatial activity patterns in primary motor and somatosensory cortices, for discriminating texture across both modalities. This study indicates that primary areas and S2 have a versatile representation of multisensory textures, which has significant implications for how the brain processes multisensory cues to interact more efficiently with our environment.

This article considers the nonlinear dynamics of coupled oscillators featuring strong coupling in 1:2 internal resonance. In forced oscillations, this particular interaction is the source of energy exchange, leading to a particular shape of the response curves, as well as quasi-periodic responses and a saturation phenomenon. These main features are embedded in the simplest system which considers only the two resonant quadratic monomials conveying the 1:2 internal resonance, since they are the proeminent source allowing one to explain these phenomena. However, it has been shown recently that those features can be substantially modified by the presence of non-resonant quadratic terms. The aim of the present study is thus to explain the effect of the non-resonant quadratic terms on the dynamics. To that purpose, the normal form up to the third order is used, since the effect of the non-resonant quadratic terms will be transferred into the resonant cubic terms. Analytical solutions are detailed using a second-order mutliple scale expansion. A thorough investigation of the backbone curves, their stability and bifurcation, and the link to the forced–damped solutions, is detailed, showing in particular interesting features that had not been addressed in earlier studies. Finally, the saturation effect is investigated, and it is shown how to correct the detuning effect of the cubic terms thanks to a specific tuning of non-resonant quadratic terms and resonant cubic terms. This choice, derived analytically, is shown to extend the validity of the saturation effect to larger amplitudes, which can thus be used in all applications where this effect is needed e.g. for control.

This paper compares the impact of two scaling methods of electric machines on the energy consumption of electric vehicles. The first one is the linear losses-to-power scaling method of efficiency maps, which is widely used in powertrain design studies. While the second is the geometric scaling method. Linear scaling assumes that the losses of a reference machine are linearly scaled according to the new desired power rating. This assumption is questionable and yet its impact on the energy consumption of electric vehicles remains unknown. Geometric scaling enables rapid and accurate recalculation of the parameters of the scaled machines based on scaling laws validated by finite element analysis. For this comparison, a reference machine design of 80 kW is downscaled with a power scaling factor of 0.58 and upscaled considering a power scaling of 1.96. For comparative purposes, optimal combinations of geometric scaling factors are determined. The scaled machines are derived to fit the driving requirements of two electric vehicles, namely a light-duty vehicle and a medium-duty truck. The comparison is performed for 9 standardized driving cycles. The results show that the maximal relative difference between linear and geometric scaling in terms of energy consumption is 3.5% for the case of the light-duty vehicle, compared with 1.2% for the case of the truck. The findings of this work provide evidence that linear scaling can continue to be used in system-level design studies with a relatively low impact on energy consumption. This is of high interest considering the simplicity of linear scaling and its potential for time-saving in the early development phases of electric vehicles

For the requirements of in-wheel traction systems, a new motor is proposed based on a specific property of multiphase machines: the ability in vector control to develop smooth torque at low speeds by using simultaneously the first and third harmonics to generate p and 3p polarities. From an initial fault-tolerant seven-phase axial–flux machine with two outer axial rotors for small vehicles such as moto/scooter is born the proposed motor just by adding magnets in the cylinder closing the two 2p-pole axial rotors of initial in-wheel motor, this addition creates thus a third radial rotor with 6p poles without changing the global volume. With an increase by 51% of the torque density, this more expensive motor can be considered in comparison with the initial in-wheel motor as a modular solution. With the same volume, a higher torque for higher acceleration and slopes can be obtained. The possibility to use different polarities with a strong non-sinusoidal back-emf without torque ripples is verified in 3D-FEM simulation and in a manufactured 28 slots – 12/36 poles prototype. Experimental results are given to prove the effectiveness of the proposal.

Many engineering systems can be described by using differential models whose solutions, generally obtained after discretization, can exhibit a noticeable deviation with respect to the response of the physical systems that those models are expected to represent. In those circumstances, one possibility consists of enriching the model in order to reproduce the physical system behavior. The present paper considers a dynamical system and proposes enriching the model solution by learning the dynamical model of the gap between the system response and the model-based prediction while ensuring that the time integration of the learned model remains stable. The proposed methodology was applied in the simulation of the top-oil temperature evolution of a power transformer, for which experimental data provided by the RTE, the French electricity transmission system operator, were used to construct the model enrichment with the hybrid rationale, ensuring more accurate predictions.

We present a unified framework for goal-oriented estimates for elliptic and parabolic problems that combines the dual-weighted residual method with equilibrated flux and potential reconstruction. These frameworks allow to analyze simultaneously different approximation schemes for the space discretization of the primal and the dual problems such as conforming or nonconforming finite element methods, discontinuous Galerkin methods, or the finite volume method. Our main contribution is twofold: first in a unified framework we prove the splitting of the error into a fully computable estimator η and a remainder, second this remainder is estimated by the product of the fully computable energy-based error estimators of the primal and dual problems. Some illustrative numerical examples that validate our theoretical results are finally presented.

Two approaches are commonly used for modelling and control of nine-phase (triple star) fault-tolerant machines with symmetrical and asymmetrical star winding configurations: The Vector Space Decomposition (VSD) and the decentralized d-q modelling. In this paper, it will be shown how the VSD approach used for machines with an Asymmetrical Star Winding Configuration (ASWC), unlike the decentralized d-q one used for machines with a Symmetrical Star Winding Configuration (SSWC), can be helpful for non-intrusive Fault Detection and Diagnosis (FDD) purposes. Supporting MATLAB/Simulink simulations are discussed.

The voltage and current outputs of a power electronic converter contain high harmonic,
especially when the required power operation point is less than the nominal one. The present paper
proposes a new space vector modulation scheme to improve this harmonic content for the overall
power range. This technique is based on an optimized distribution of the zero vectors during the
sampling time. Firstly, a vector spatial approach of the voltage flux harmonic is analytically
synthesized. Hence, the obtained flux harmonic trajectories are optimized somehow to minimize the
distance between the gravity center of this trajectory and its origin, which gives the exact du- ration
of the zero vectors. The obtained simulation and experimental results show an improved harmonic
content of the output converter even for low modulation index and an enhanced converter current
waveform. The results confirm the superiority of the proposed strategy compared to the previously
developed.

The energy sector is undergoing a profound transformation
to tackle climate change issues rapidly and efficiently.
The development of decentralized renewable energy and the
electrification of the transport sector are two major aspects
affecting electrical grids. This paper presents a novel energy
management strategy that supervises controllable loads like
electric vehicles and electric water heaters in a distribution
grid to reduce energy transmission costs and promote the local
consumption of renewable energy. The proposed strategy uses
day-ahead forecasts of energy production and consumption to
schedule future load profiles. It also considers potential grid
constraints using a real-time co-simulation approach. The estimated
constraints are mitigated by modifying the controllable
loads’ dispatch or adjusting their power set-points. The system’s
performance is finally evaluated on a real distribution grid model
during days that present the most voltage constraints in the year.

The need for electrical machines is growing in a wide range of applications nowadays, such as for energy production, automotive, marine, and medical equipment, etc. The reliability, efficiency, performance and operational safety are always critical issues, which implies that the monitoring and analysis during the operation of the equipment need to be strengthened. In general, more sensors can give higher accuracy of the estimated physical quantity, but bring a more expensive cost. To address this issue, an algorithm principally based on the parameterized background data-weak (PBDW) method is proposed and adopted in this work to optimize both the number and the location of sensors. Besides, to further investigate the performance of the proposed algorithm, a prototype concerning an anisotropic magnetostatic problem is studied as an example for the placement of magnetic sensors. The numerical experiments shows that the proposed method can achieve very satisfactory results in different aspects.

High-frequency and high-power density converters are essential for many applications such as automotive and more electric aircraft. To improve power density, planar magnetic components are increasingly used in power electronic converters owing to their advantages, such as less high-frequency losses, repeatability, and better thermal performance compared to conventional wound components. Considerable attention has been paid to their electrical performance. However, the thermal aspects are essential for enhancing completely their performance. Currently, there is an increasing interest in these critical aspects of high-density power converters. This paper presents a literature review of studies on the thermal modeling of planar magnetics. The papers were organized according to the model type and analyzed to highlight their merits and limitations. A multicriteria comparison of the studied papers was performed. Moreover, the key points and issues related to the thermal modeling are addressed to guide designers in enhancing the thermal aspects of planar magnetic components.

Skin integrity assessment is a very important matter in the nursing care, especially for patients with low mobility. However, the methodology of skin analysis is limited by a lack of reliable yet portable tools. In this paper, a new sensor is proposed for skin mechanical impedance characterisation, aiming to provide an objective assessment of skin health. The device consists in a microcontroller connected to a Langevin transducer. Using the vector control method, the reference vibration of the transducer is assured, and the mechanical impedance is observed. To ensure the repeatability of the measurements, tests in the morning and in the afternoon were taken. To verify if the device can distinguish sites with different mechanical properties on the same body, tests were made on 2 different body sites: the palm of the hand and the volar forearm. Measurements of skin hydration were also taken, to find a potential correlation of these parameters and skin acoustical mechanical impedance. Results have shown that the measurements provided by the device are mostly reliable, and reveal a fair correlation between mechanical impedance and hydration, in the level of stratum corneum, the outermost layer of skin. Also, the device is able to show the difference on the mechanics of the skin in the different body sites tested, independently of the hydration.

Networked microgrids is a cluster of local grids that can be connected through a weak network and can provide ancillary services. On a system point of view, it is desirable that every microgrid exhibits a behaviour at the Point of Common Coupling (PCC) which enables to share active and reactive powers with other grids. This paper proposes a Model Predictive Supervisor that encompasses internal objectives and enforces a virtual droop control at the PCC. The supervisor uses a prediction module based on a model of the microgrid and an outer loop which supplies the PCC powers with respect to the aggregated capability diagram at the PCC. For a weak network, this diagram depends on the PCC voltage that varies with time, generating a set of time varying non-linear constraints. The supervisor generates the references to control the local distributed generators which are inside the microgrid. Through the three steps developed in this paper, the need for model based control is highlighted and a Model Predictive based Controller proposed and validated from simulations.

Greater numbers of power electronics (PEs) converters are being connected to energy systems due to the development of renewable energy sources, high-voltage transmission, and PE-interfaced loads. Given that power electronics-based devices and synchronous machines have very different dynamic behaviours, some modelling approximations, which may commonly be applied to run transient simulations of transmission systems, may not be optimal for future grids. Indeed, the systematic utilisation of the phasor approximation for power lines, implemented in most transient simulation programs, is increasingly not appropriate anymore. In order to avoid the requirement for full electromagnetic transient simulations, which can be resource-demanding and time-consuming, this paper proposes a combination of an event-based state residualisation approximation and the Kron reduction technique. The proposed technique has the advantage of allowing accurate transient simulations based on the optimal reduction of the number of state variables, depending on the observed variables, the considered events, and the tolerated approximation error, along with simplifying power systems equations for accelerated simulations.

This article presents a bridge between topology optimization (TO) and additive manufacturing. On the one hand, it presents an algorithm that considers the design variables as binary and then solves the problem by binary linear programming to optimize a ferromagnetic core. On the other hand, a 3-D printing process is developed to manufacture the shapes obtained by TO. Finally, these magnetic parts are characterized through electrical measurements.

This paper proposes a robust decoupling power algorithm based on a doubly fed induction generator (DFIG) for variable speed
wind-turbine (WT). The DFIG rotor circuit is fed by the direct matrix converter (DMC), which presents several features such as no
need to the dc-bus voltage, sinusoidal supply, rotor side waveforms, bidirectional power flow, and adjustable input power factor.
The 18 bidirectional switches are controlled using the Venturini modulation technique. On the other hand, the DFIG stator circuit is
connected directly to the grid. The nonlinear control strategy based on feedback linearization is applied to control the stator power
(Ps and Qs) independently using the rotor quadrature and direct currents (irq and ird), which present the images of the previous
stator powers. Some limitations appear in the power algorithm using the conventional pi controller, especially in power tracking,
error, and quality. In this context, the model reference adaptive controller (MRAC) presents an alternative solution, a robust and
efficient controller proposed instead of the pi controllers to control stator powers. Finally, the simulation results confirm that the
proposed algorithm could work under hard conditions and demonstrate that the wind energy conversion system (WECS) provides
enhanced dynamic responses in transient and steady states and good power quality delivered to the grid.

Synchronization of audio-tactile stimuli represents a key feature of multisensory interactions. However, information on stimuli synchronization remains scarce, especially with virtual buttons. This work used a click sensation produced with traveling waves and auditory stimulus (a bip-like sound) related to a virtual click for a psychological experiment. Participants accomplish a click gesture and judge if the two stimuli were synchronous or asynchronous. Delay injection was performed on the audio (haptic first) or the click (audio first). In both sessions, one stimulus follows the other with a delay ranging from 0−700ms . We use weighted and transformed 3-up/1-down staircase procedures to estimate people's sensitivity. We found a threshold of 179ms and 451ms for the auditory first and haptic first conditions, respectively. Statistical analysis revealed a significant effect between the two stimuli' order for threshold. Participants' acceptable asynchrony decreased when the delay was on the haptic rather than on the audio. This effect could be due to the natural experience in which the stimuli tend to be first tactile and then sonorous rather than the other way around. Our findings will help designers to create multimodal virtual buttons by managing audio-tactile temporal synchronization.

Performing a climate impact assessment of vehicles is essential for comparing different powertrain options during an entire vehicle life. Life Cycle Assessment (LCA) is used to estimate these effects over a vehicle's lifecycle, including manufacturing, usage, and end-of-life phases. LCA comprises several indicators, such as the Global Warming Potential (GWP). Generally, LCA or GWP studies use manufacturer-reported standard cycle data to estimate the energy consumption of vehicles. In this article, we develop diesel, gasoline, and electric vehicle simulation tools using the Energetic Macroscopic Representation formalism to evaluate that practice. These simulations are validated with actual, measured driving cycles. The simulations are then used to compare the calculated GWP from real, measured driving cycles relative to standard driving cycles used as industry benchmarks. The results show that standard driving cycles consistently underestimate the benefit of switching from fossil fueled vehicles to electric vehicles. Finally, a sensitivity analysis of the battery life duration is included in this work. It shows that the replacement or second life of batteries is also a key parameter in the GWP advantages of electric vehicles.

In this paper, a methodology is proposed for studying the current collapse effects of
Gallium Nitride (GaN) power diodes and the consequences on the dynamic on-resistance (RON).
Indeed, the growing interest of GaN based, high frequency power conversion requires an accurate
characterization and a deep understanding of the device’s behaviour before any development of
power converters. This study can ultimately be used to model observed trap effects and, thus,
improve the equivalent electrical model. Using an in-house circuit and a specific experimental
setup, a current-collapse phenomenon inherent to gallium nitride semiconductor is studied on planar
650 V—6 A GaN diodes by applying high voltage stresses over a wide range of temperatures. With
this method, useful data on activation energy and capture cross section of electrical defects linked
to dynamic RON are extracted. Finally, the origins of such defects are discussed and attributed to
carbon-related defects.

In this article, we propose a new concept for tuning a resonant piezoelectric shunt absorber thanks to the use of a nonsmooth electronic component. It consists in adding a voltage source in the resonant shunt circuit, which is a bilinear function of the voltage across the piezoelectric patch. The main advantage is the ability to change the electrical resonance frequency with the bilinear component gain, enabling a tuning as well as a possible reduction in the required inductance value. Furthermore, because of the intrinsic nonlinear nature of the bilinear component, a multi-harmonic response is at hand, leading to a nonlinear coupling between the mechanical and electrical modes. Two particular tunings between the electrical and the mechanical resonance frequencies are tested. The first one is one-to-one, for which the electrical resonance is tuned close to the mechanical one. It is proved to be similar to a classical linear resonant shunt, with the additional tuning ability. The second case consists in tuning the electrical circuit at half the mechanical resonance, leading to a two-to-one (2:1) internal resonance. The obtained response is also found to be similar to a classical resonant shunt near the main resonance. In either case, the shunt performances are analytically and numerically studied, leading to optimal values of the design parameters as well as an estimation of the amplitude reduction provided by the shunt. Finally, experimental validation is proposed, targeting the damping of the twisting mode of a hydrofoil structure, in which the bilinear component is realized with a diode.

In this study, we present a theoretical and experimental analysis of an antiresonance detuning correction for a nonlinear piezoelectric shunt absorber based on a two-to-one internal resonance. Thanks to this purely nonlinear feature, the oscillations of the primary system become independent of the forcing at a particular antiresonance frequency, thus creating an efficient reduction of the vibration. Past works of the literature present the design of the piezoelectric shunt and show that it is subjected to a softening behavior that detunes the antiresonance frequency as a function of the amplitude and thus degrades the performance. It is also shown that this softening behavior is caused by some non-resonant terms present in the equations, linked to the piezoelectric coupling. To counteract this undesired effect, we propose in this work to add a cubic nonlinearity in the shunt circuit, in addition to the quadratic one already present. Its tuning is based on a normal form analysis already published, which shows how cubic nonlinearities can cancel the effect of quadratic non-resonant terms. The present article describes the main features of the theory and focuses on the experimental proof of concept of this antiresonance detuning correction as well as the analysis of its range of validity. It is applied to the damping of the first bending mode of a hydrodynamic foil structure.

The deployment of DC fast charging stations (DCFCSs) in cities requires costlyrein-forcement of low‐volt age (LV) distribution grids, due to the high power required. It results in high investments for the station operator as well as for the distribution system operatorand profitability of such projects. In this study, a novel concept of fast charging station which reduces the connection to the grid is presented.This station uses Vehicle‐to‐vehicle (V2V) power transfer from a fleet of car sharing electric vehicles to provide a high charging power while mitigating the power demand on the grid. Based on data from a car sharing operator in the city of Paris, a simulation model of a combined carsharing/V2V fast charging system is proposed, allowing to simulate car sharing trips and V2Vtransfers. The reduction of the grid connections required to provide fast charging is evaluated and the impact of the repeated discharges on the level of service ofthe car sharing system is discussed. Moreover, simulation of LV distribution grids allows to compare the grid losses of the V2V system with conventional DCFCSs.

This paper presents a measurement-based under-frequency load shedding scheme that considers time delays, measurement uncertainties, and communication network faults. Using a moving first-degree polynomial function, an iterative approach to estimate the frequency nadir and the associated frequency nadir time is proposed. Then, a novel method to simultaneously estimate the power imbalance and the system inertia constant is developed. According to an analytical basis, a base system is selected from a set of pre-defined base systems to guarantee accurate power imbalance estimation. Finally, a mathematical index is investigated to calculate a threshold for the generation-load power imbalance beyond which loads should be shed. Further, a systematic approach for specifying the amount of load to be shed in each transmission bus of the system is proposed. The effectiveness of the proposed methodologies is examined on both simulated and actual measured data from 9 historical power system disturbances in a national power grid.

Due to the advancement in the development of semiconductors used in the power converters, the printed circuit boards (PCBs) require an in-depth study of their electromagnetic behavior. To characterize the behavior of the PCBs, the Darwin model is employed, which can take into account all the coupled effects, namely resistive, inductive, and capacitive effects, at the intermediate frequencies. Nevertheless, the study of particular structures having a geometric dimension smaller than the others can create meshing difficulties. The modeling of thin structures by the finite element method requires the optimization of the mesh. To circumvent this issue, the shell elements for both node and edge elements are applied in this work. Finally, to validate the proposed approaches, two PCBs with different geometries are studied in both time and frequency domains, where the measurements for a single PCB are provided to compare with the numerical results.

This paper describes an electromechanical handheld probe dedicated to skin biomechanics characterization.
This probe is composed of two piezoelectric bending actuators that control tip displacement. Simultaneous force
and displacement sensing is achieved by integrating two pairs of resistive strain gauge sensors. Piezoelectric
hysteresis, however, compromises the accuracy of force sensing. To improve force sensing, a hysteresis model
is introduced. The hysteresis behavior of piezoelectric actuators is usually described between the input voltage
and output displacement. The influence of external force is rarely discussed. Considering the combined effects
of the electric field and the external stress, we model hysteresis with the instantaneous displacement relying
on the Bouc–Wen model. Experimental and simulation results show that the hysteresis model can predict
bender behavior even driven by multi-harmonic voltages. Based on this hysteresis model, the hysteresis
compensation strategy is validated at no load and loaded conditions (a spring load). However, to simplify
the compensation process, another original strategy is proposed, relying on a closed-loop displacement control.
Results demonstrate that the second approach also improves the accuracy of force sensing. Finally, preliminary
measurements performed on the real skin show promising results.

Schottky contacts on fluorine implanted AlGaN/GaN heterostructure with ideality factor
close to unity and low on-voltage threshold are presented in this paper. A SF6 plasma anode
pre-treatment followed by a specific low-temperature annealing is also compared to a nonannealed sample. In addition, physical-model parameters are extracted by means of
cryogenic temperature measurements to understand the conduction mechanisms involved
in annealed diodes, showing better DC performances than their non-annealed counterparts.
Furthermore, the annealing induces a decrease of the ideality factor, which sets the fieldenhanced thermionic emission as the main conduction mechanism, and reduces the
tunneling reverse current leakage. This effect is attributed to the recovering of the plasmainduced damages.

Nondestructive testing (NDT) of industrial steel products is commonly used to detect defects such as cracks using among other methods, electromagnetic techniques. When properly calibrated, these NDT can be adapted to evaluate the mechanical properties of steels. It is especially of prime importance when rigorous quality control must be achieved for high performance steels. In this context, the proposed article deals with the investigation of the Magnetic Barkhausen Noise (MBN) to characterize the tensile properties of high mechanical performance martensitic steels.

The magnetic behavior of a lamination stack made of grain-oriented electrical steel (GOES) is investigated under non-conventional 3D magnetic flux excitations. An experimental demonstrator has been designed to study a normal orientation of the magnetic flux path, with regard to the lamination plane, combined with different in-plane orientations of the easy magnetization axis of the lamination stack. The results in terms of the magnetic flux distribution and the iron losses are presented and discussed.

This paper deals with the temperature-dependent modelling of iron losses in the context of magnetic ageing of electricals steel used in high power electrical machines. First, two electrical steel sheet grades were heat treated at three temperatures in order to study the ageing effect evolution as a function of temperature. Results show a significant increase in iron losses for both steel grades. Then, considering the link between the macroscopic magnetic properties evolution (effect) and the microscopic precipitation (cause), the Johnson – Mehl – Avrami – Kolmogorov (JMAK) law describing the kinetics of precipitation was applied to model the time evolution of magnetic ageing. By coupling this model with the Arrhenius’ law, a model is developed to be able to predict the ageing for several temperature levels.

The performance and energy efficiency of electro-mechanical converters are strongly bound to the properties of their magnetic cores. The latter are mostly made from stacked laminations of soft magnetic materials, such as Fe3%Si, which limits the core geometry design. However, when complex geometries are required, usually forging processes may be employed but with very low silicon steels (<0.5%) to be able to forge the steel. In that case, the low silicon content yields to higher electrical conductivity and then to higher eddy current loss. In this work, an additive manufacturing technique allowing to build complex geometries is studied with Fe3%Si magnetic materials. The fabrication process allows to obtain green parts which are then densified through debinding and sintering steps. The magnetic characterization is performed on toroidal cores and allows to observe a high level of magnetic induction and relative permeability. Finally, the impact of the printing strategy on the magnetic performances is investigated.

This paper deals with the analysis of the magnetic properties degradation following an industrial impregnation process of electrical steels employed in stators of large generators. First, the impregnation process is studied directly on industrial stators to emphasize the significance of the process effect. Then, to have a controlled approach of the impregnation conditions, laminated ring cores were subjected to the same process but for different configurations. The ring cores were magnetically characterized to highlight the influence of the resin on the magnetic properties. Also, in order to distinguish the effect of the resin from potential other phenomena during the curing phase (i.e. the ageing effect), an experimental protocol is proposed: the results allow to emphasize the impact of such process on the magnetic properties.

In this paper, we make a comparative study of fuzzy logic and boolean logic energy management strategies (EMSs) for an
hybrid electric vehicle (HEV) with parallel architecture made up mainly of an electric motor (EM) and an internal combustion engine (ICE). EM is used as a main propulsion system for the vehicle. However, the ICE is used as a backup system. This study is developed to manage the energy flow between the two sources by ensuring a balance between the generated and consumed powers, injected or absorbed into the battery and minimizing the ICE operation in order to reduce the fuel consumption and CO2 emission. The purpose of this study is to investigate the different scenarios for fuzzy logic and classical logic strategies under the Normalized European Drive Cycle (NEDC), NEDC cycle for 1-hour, and combined cycle of Worldwide harmonized Light vehicles Test Procedures (WLTP) and Assessment and Reliability of Transport Emission Models and Inventory Systems (ARTEMIS) cycles. The change of test conditions from NEDC to WLTP and ARTEMIS was shown to lead to a significant reduction of the fuel consumption and CO2 emission using the fuzzy logic control with results that may attend 50% increase of CO2 emissions reduction VS the results of boolean logic control.
Simulations are made using MATLAB/ Simulink software. Results of both strategies are presented and discussed in this paper.

The manufacturing processes of electrical machines may lead to significant degradation of the magnetic properties of their magnetic core (stator, rotor) performances and, as a consequence, to a decrease of their energy efficiency. While the effects of some processes (cutting, welding …) are widely discussed in the literature, this is not the case with the compaction process although it is systematically used to maintain the assembly of electrical steel sheets that compose the magnetic circuits. In addition to the conventional one, a specific compaction process exists for high-power electrical machines. After an introduction, the paper firstly deals with the two studied processes (conventional, specific). Then, an experimental mock-up to study the impact of the two configurations on the magnetic properties (iron losses, normal magnetization curve) is presented. This mock-up is the first, in the literature, that allows to study the effect of a controlled compaction mechanical stress on magnetic properties. Obtained results in both configurations highlight a magneto-mechanical effect that is not reported in the literature where these effects are commonly considered following in-plane mechanical stresses. This paper presents a magneto-mechanical model, taking into account the compaction stress effect, as well as a modelling protocol to model the effect of 3D mechanical stress on magnetic properties, which has never been done in the literature.

The opening up of the railway to competition in Europe has been accompanied by many technical challenges never before
seen in the railway field. One of these challenges concerns precise energy metering. As European railways have been a monopoly until now, the current systems can only measure the energy consumption of a single operator. In accordance with European law, the installation of an energy meter has been mandatory in new or refurbished rolling stocks since 2014. Nevertheless, these energy meters are still not fully reliable, with misreadings and missing readings being common occurrences. To address the problem of energy metering data reliability, this paper presents a method for validating the reading measurement based on a physical model and validates it in two different case studies. For the issue of energy
metering data availability, different estimators are developed, and their performance are shown with the aim of calculating the
missing consumptions for both case studies. Finally, the paper suggests how these methods may be implemented in other types of trains.

A numerical issue arises when we extend the convolutional neural network (CNN) U-net to the anisotropic magnetostatic field computation. The output magnetic field has a significant gradient with respect to the input geometry parameter, which introduces inevitable errors in the training process to degrade the performance of deep learning (DL). To address this issue, the subset selection approach is utilized to divide the whole database into serval subsets, where the samples are assigned according to the gradient between the input and output. Then these subsets with different sample densities are combined into a global one. Taking the uniform dataset with the same sample size as a comparison, the influence of subset selection on DL is investigated by comparing the performance of CNN on different datasets. Numerical experiments illustrate that the adaptive subset selection can be employed to improve the accuracy and efficiency of the CNN network.

As one of the key components, low-speed direct-drive in-wheel machines with high compact volume and high torque density are important for the traction system of electric vehicles (EVs). This paper introduces four different types of outer-rotor permanent magnet motors for EVs, including one five-phase SPM machine, one three-phase IPM machine with V-shaped PMs, one seven-phase axial flux machine (AFM) of sandwich structure and finally one hybrid flux (radial and axial) machine with a third rotor with V-shaped PMs added to the AFM. Firstly, the design criteria and basic operation principle are compared and discussed. Then, the key properties are analyzed using the Finite Element Method (FEM). The electromagnetic properties of the four fractional slot tooth concentrated winding in-wheel motors with similar dimensions are quantitatively compared, including air-gap flux density, electromotive force, field weakening capability, torque density, losses, and fault tolerant capability. The results show that the multi-phase motors have high torque density and high fault tolerance and are suitable for direct drive applications in EVs.

This work presents the control of a piezoelectric interface that combines two vibration modes of a plate to render the haptic feeling of a button click. By principle, the two vibration modes create an elliptical motion of particles of a beam that can induce a lateral force to the fingerpulp. In this device, the synchronization of the modes’ vibrations is essential, and can be obtained with a closed loop control. In the paper, we present the control in the (d,q) frame, because it can ensure the dynamic performances to achieve a compelling haptic feedback, yet being robust besides the external disturbances produced by the user’s finger. The proposed method could achieve a 2 ms response time, and the haptic feedback was perceived by 100% of users in a psychophysical study.

The fast development of renewable energies leads to an increase in the power electronics penetration in transmission systems. This is particularly true if one considers a 100% renewable energies power system, where wind and solar photovoltaic energies, which make most of the renewable energies connections today, are connected to the grid through power electronics converters. Because power electronics-based generators and synchronous machines-based generators have very different dynamic behaviours, some approximations usually used to run transient simulations of transmission systems might not be optimal for future grids. The systematic use of the phasor approximation applied to the power lines, implemented in most of the Transient Simulation Programs, is indeed not relevant any more. To avoid the use of Electromagnetic Transient simulations, that are resource-demanding and time-consuming, this paper presents a novel Model Order Reduction technique for large grids with a high penetration of power electronic devices. Compared to the classical phasor approximation, this event-based state residualization approximation allows accurate transient simulations and at the same time an optimal reduction of the number of the system's state variables depending on the observed variables, the considered events and the tolerated approximation error.

In this paper, a reliable methodology is proposed in order to implement and validate a Model Predictive Control (MPC) scheme on an actual Voltage Source Converter (VSC) integrated in a scale-down multi-terminal DC grid. The objective of the investigated MPC controller is to enable AC frequency support among two asynchronous AC areas through a High Voltage Direct Current (HVDC) grid, while considering physical constraints, such as maximum and minimum DC voltage. A systematic and accurate implementation strategy is proposed, based mainly on the Hardware In the Loop (HIL) and Power Hardware In the Loop (PHIL), leading to the real-life testing on VSC, controlled by a classical microcontroller. The technical problems during the implementation process, as well as the proposed solutions, are described in detail through this paper. This procedure is deemed valuable to bridge the gap between offline simulation and the actual implementation of such advanced control scheme on experimental test rig.

For non-sinusoidal electromotive force (NS-EMF) multiphase machines, this paper proposes a new strategy and control scheme to guarantee smooth torque under an open-phase fault. Notably, the conventional proportional-integral (PI) controllers implemented for vector control in healthy mode can be used in the faulty mode. The strategy is based on reduced-order transformations while the control scheme applies a simple artificial intelligence algorithm using a specific online-trained Adaptive Linear Neuron (ADALINE). Indeed, the inputs of ADALINE require the knowledge of rotor position and NS-EMF harmonic rank to optimize the learning time. The proposed strategy and control scheme are tested on a seven-phase machine with a strong Total Harmonic Distortion (THD) of NS-EMFs, containing numerous harmonics Hk (THD=38% with 100% H1, 32.3% H3, 9.4% H7, 12.5% H9, 10.3% H11). Numerical and experimental results are presented in this paper. This paper is accompanied by a video demonstrating the experimental results.

The energy consumption of electric vehicles depends on the traction energy but also on the thermal comfort energy. Some studies lead to the estimation of this energy consumption from real measurements on different driving and climatic conditions. However, those results rely on a large number of vehicle tests, which is time consuming. Moreover, the impacts of the different subsystems cannot be differentiated in such global studies. A flexible simulation tool can help to analyze the impact of the different parts of a vehicle. This paper proposes a multi-physical parametrized model of an electric vehicle including the traction and comfort subsystems. A flexible model of a Renault Zoe is developed thanks to the energetic macroscopic representation. This model is validated by experimental tests of the real vehicle. Then, the impact of the HVAC (heating, ventilation, and air conditioning) subsystem is studied for different driving cycles and climatic conditions. In very cold conditions, the use of the HVAC subsystem represents an increase of up to 248% of the total energy consumption, compared to summer conditions.

In this paper, a semi-passive nonlinear piezoelectric shunt absorber is presented, aiming at attenuating the vibration of a resonant elastic structure under external excitation. This is done by connecting the elastic structure to a nonlinear shunt circuit via a piezoelectric patch. The nonlinear shunt circuit consists of resonant circuit that includes a quadratic non-linearity. A particular tuning of the natural frequency of the shunt enables to create a two to one internal resonance. This generates a strong coupling between the mechanical mode and the electrical mode, leading to replace the mechanical resonance with a nonlinear antiresonance associated with an amplitude saturation, thus leading to an efficient vibration reduction. In this paper, we first propose a theoretical model that is expanded onto a suitable electromechanical modal basis and reduced to the two modes of interest, nonlinearly coupled by quadratic terms. Then, analytical solutions are obtained by the multiple scale method and compared to a reference numerical solutions stemming from the harmonic balance method. This enables to investigate the performance of the system in term of vibration absorption as well as giving design rules to tune the nonlinear shunt and to choose the free parameters of the system.

High-frequency power converters need electromagnetic interferences filters using common and differential mode chokes with low parasitic capacitance to comply with the electromagnetic compatibility standards. This article proposes a modeling method of this capacitance and ways to minimize it. The studied components are ring core inductors with magnetic materials considered as perfect conductors or with high permittivity, such as nanocrystalline material and most Mn-Zn ferrite materials. In comparison to other work in the literature, the proposed approach takes into account the curvature of the turn, in addition to the coating of the core and the insulation layer of the wire. The hypotheses, used in this article to simplify the real geometry, are compatible with two-dimensional (2-D) approaches to compute the parasitic interturns and turn–core capacitances. These capacitances are evaluated thanks to the 2-D finite element method. The obtained model allows accurate evaluation of the effect of turn–core space on the parasitic capacitance, and enables to reduce its value with a limited impact on the volume of the magnetic component.

This article deals with the modelling of iron losses due to the magnetic ageing of electrical steels used in energy conversion devices. This phenomenon is the consequence of irreversible mechanisms in the material which can be triggered by the operating temperature of electrical devices. At first, an experimental study is carried out at 180◦ C in order to assess the effect of isothermal ageing on electromagnetic properties of a magnetic steel sample. The results show that, during the thermal ageing, the hysteresis losses and the coercive field increase. These experimental observations, mainly caused by the formation of precipitates at the material microstructural scale, are then discussed. Considering the link between the effect of magnetic ageing on macroscopic magnetic properties (effect) and the microscopic precipitation (cause), the Johnson – Mehl – Avrami – Kolmogorov (JMAK) law describing the kinetics of precipitation was applied to model the time evolution of magnetic ageing. Once this approach was validated, it is proposed to integrate the JMAK law in the Steinmetz iron loss model.

Nowadays, additive manufacturing of metallic materials is most often carried out using expensive and complex tools that leave the user with limited control and no possibility of modification. In order to make the printing of metal parts more accessible to small structures but also better suited for academic research, the use of a mixture of thermoplastic polymer and metal powder is a good solution as many granular feedstocks already exist for Metal Injection Molding applications. To perform the shaping process, the Fused Granular Fabrication 3D printing technology is set up by diverting the use of a feedstock in the form of pellets that are directly inserted into the print head. This solution, which is less costly, is implemented here by modifying a mid-range printer, the Tool Changer from E3D, and by making the hardware and software adaptations to mount a compact granulates extruder on it, which is also available on the market. The polymer portion present in the green part can then be removed in order to perform the heat treatments that will densify the powder by sintering and give a fully metallic dense object.

This paper describes the relations between microstructure, mechanical properties, and electromagnetic behavior of carbon steel wires submitted to different thermomechanical treatments. The
electrical resistivity and bulk magnetic properties are determined through resistivity measurements down to 2 K and magnetic hysteresis loop measurements. In addition, magnetic domains are imaged by magnetic force microscopy despite the complex microstructures. The electromagnetic properties are mainly related to changes in the volume fraction, morphology, and distribution of the cementite phase within the α-ferrite matrix. Electrical conductivity and magnetic permeability increase in the order of martensite, tempered martensite, pearlite, proeutectoid ferrite-pearlite, spheroidite, and ferrite microstructures. The increase in carbon concentration enhances the electrons localization at atomic sites, assisting the covalent character of Fe–C interatomic bonds and thereby reducing conductivity. Moreover, the α-Fe3C interfaces that act as a physical barrier for dislocation slip in ferrite, affecting also the main free-paths for conductive electrons and magnetic domain walls displacements within the materials. As the electromagnetic behavior of steels results from individual contributions of microstructural elements that are often intrinsically related to one another, a careful interpretation of both electrical and magnetic responses is critical for a proper application of quality and process monitoring methods of carbon steel wires.

Convolutional neural networks (CNN) have shown great potentials and have been proven to be an effective tool for some image-based deep learning tasks in the field of computational electromagnetism (CEM). In this work, an energy-based physics-informed neural network (EPINN) is proposed for low-frequency electromagnetic computation. Two different physics-informed loss functions are designed. To help the network focus on the region of interest instead of computing the whole domain on average, the magnetic energy norm error loss function is proposed. Besides, the methodology of energy minimization is integrated into the CNN by introducing the magnetic energy error loss function. It is observed that the introduction of the physics-informed loss functions improved the accuracy of the network with the same architecture and database. Meanwhile, these changes also cause the network to be more sensitive to some hyperparameters and makes the training process oscillate or even diverge. To address this issue, the sensitivity of the network hyperparameters for both physics-informed loss functions are further investigated. Numerical experiments demonstrate that the proposed approaches have good accuracy and efficiency with fine-tuned hyperparameters. Furthermore, the post-test illustrates that the EPINN has excellent interpolation performance and can obtain good extrapolation results under certain restrictions.

In this article, several modes are controlled simultaneously both in phase and amplitude on an haptic display. To achieve this, modulation/demodulation control combined with mixed spatial/frequency filters is developed. It is then applied to produce a predefined velocity field both in space and time on a plate. The experimental results show good agreement with theory.

The Darwin model, which simultaneously incorporates resistive, capacitive, and inductive effects but neglects the radiation one, has recently attracted more and more attention in the research area. For our industrial application needs, the finite-element (FE) system to solve derived from the Darwin model generally has a large size, which is beyond the capabilities of the direct solvers due to the memory limitation. In this work, a specially designed formulation amenable to an iterative solver is proposed for industrial applications. Moreover, a detailed comparison of different cases is carried out on two different examples.

Optimization using finite element analysis and the adjoint variable method to solve engineering problems appears in various application areas. However, to the best of the authors’ knowledge, there is a lack of detailed explanation on the implementation of the adjoint variable method in the context of electromagnetic modeling. This paper aimed to provide a detailed explanation of the method in the simplest possible general framework. Then, an extended explanation is offered in the context of electromagnetism. A discrete design methodology based on adjoint variables for magnetostatics was formulated, implemented, and verified. This comprehensive methodology supports both linear and nonlinear problems. The framework provides a general approach for performing a very efficient and discretely consistent sensitivity analysis for problems involving geometric and physical variables or any combination of the two. The accuracy of the implementation is demonstrated by independent verification based on an analytical test case and using the finite-difference method. The methodology was used to optimize the parameters of a superconducting energy storage device and a magnet press and the optimization of the topology of an electromagnet. The objective function of each problem was successfully decreased, and all constraints stipulated were met.

Robustness and reliability of modern synchronous motors require an accurate design of the permanent magnets (PM) while accounting for the motor operating conditions (demagnetizing field, temperature). In this paper, the important attribute of a PM non-linear demagnetization model within a finite element method (FEM) simulation environment is clearly emphasized. To do so, starting from experimental measurement achieved on a NdFeB PM, a toolbox baptized “PM-Demag” has been developed. This toolbox manages the PM history and updates the PM B(H) characteristics depending on the temperature and the PM working point. Finally, a relatively straightforward coupling is implemented with a FEM software and applied to a simple study case. Results show local magnetization loss in the PM due to the combination of both the temperature and the demagnetizing field.

Regularly used in power transformers, grain-oriented (GO) steels are also usually chosen for the manufacturing of the stator cores of hydro and turbo-generators. These steels are renowned for their high magnetic performances in the rolling direction (high permeability and low magnetic losses). Nevertheless, in a turbo-generator where GO steels are employed to reduce the size of the stator core, the magnetic flux flows through several successive directions within the plane of the steel. So, the anisotropic behavior of the GO steel has to be considered in the design step of the related devices in order to improve their energy efficiency as well as their diagnosis based on modeling. In this paper, an anisotropic phenomenological iron loss model, quite recently developed, has been studied and successfully implemented in a finite element method (FEM) simulation environment. The implementation has been validated against experimental data achieved on an industrial conventional GO grade typically used in turbogenerators. The results show a good agreement of the computational results with the experiments for both quasi-static and dynamic regimes.

The series–parallel architecture is the most interesting for hybrid electric vehicles, allowing the lowest fuel consumption. Unlike passenger cars, this architecture is not commercially available on the heavy-duty vehicles market. This is due to technical limitations associated with unsufficient load capability of the geartrain. To address this issue, new transmissions, such as the electrical variable transmission, have been developed. The novelty of this paper relies on the hybridization of a long-haul truck using the electrical variable transmission. This study aims to investigate the potential of using this new transmission for trucks. For that aim, fuel consumption benchmarking of three powertrain topologies is performed, considering: (a) a gearless topology; (b) a geared topology that uses one gearbox inserted between the engine and the mechanical input port of the electrical variable transmission; (c) a geared topology similar to the second one, but, with an additional multi-stage gearbox inserted to the mechanical output port of the electrical variable transmission. For a fair comparison between the different topologies, a bi-level optimization process has been used, incorporating the optimization of both components sizing and control. Results show that the fuel consumption of the gearless powertrain is higher than the engine-powered truck due to higher losses in the electrical variable transmission. While maximum fuel reduction of 14.2% was obtained by a geared topology that uses two gearboxes. Furthermore, emphasis is given to understand the effect of the powertrain component sizing on fuel consumption. Depending on the defined sizing, a possible fuel reduction is achieved from 3.3% to 14.2% for the two geared topologies. The reduction of CO2 emissions is found to be proportional to the fuel savings. Considering a long-haul mission, the last findings prove that the electrical variable transmission exhibits potential to reduce fuel consumption, if an adequate powertrain topology and its sizing are well defined.

Parametrically excited oscillators are used in several domains, in particular to improve the dynamical behaviour of systems like in the case of the parametric amplification or parametric energy harvesting. Although dry friction is often omitted during system modelling due to the complexity of its nonsmooth nature, it is sometimes necessary to account for this kind of damping to adequately represent the system motion. In this paper, it is proposed to investigate the effect of dry friction on the dynamical behaviour of a nonlinear parametric oscillator. Using the pendulum case as example, the problem is formulated according to a Mathieu-Duffing equation. Semi-analytical developments using the harmonic balance method and the method of varying amplitudes are used to find the solutions of this equation and their stability. These results are validated thanks to a comparison with time integration simulations. Effects of initial conditions on the basins of attractions of the solutions are also studied using these simulations. It is found that trivial and non-trivial solutions of the oscillator including dry friction are not connected, giving birth to isolated periodic solutions branches.Thus, both initial displacement and phase between the excitation and the oscillator displacement must be carefully chosen to reach periodic solutions. Finally, a method based on the energy principle is used to find the critical forcing amplitude and frequency needed to obtain the birth of nontrivial solutions for the nonlinear parametric oscillator including dry friction.

Fault tolerance has been known as one of the main advantages of multiphase drives. When an open-circuit fault happens, smooth torque can be obtained without any additional hardware. However, a reconfiguration strategy is required to determine new reference currents. Despite advantages of non-sinusoidal electromotive forces (NS-EMFs) such as high torque density, multi-harmonics existing in NS-EMFs cause more challenges for control, especially under faulty conditions. Therefore, to guarantee high-quality vector control of multiphase drives with multi-harmonic NS-EMFs, this two-part study proposes control schemes using adaptive linear neurons (Adalines) to adaptively eliminate torque ripples. The proposed simple Adalines are efficient because of taking advantage of the knowledge of rotor position and of torque harmonic rank induced by the NS-EMFs. The control scheme using an Adaline for healthy mode was described in part I of this study. In this second part, the control scheme using another Adaline for an open-circuit operation, under the impacts of multi-harmonics in NS-EMFs, is proposed. Notably, smooth torque and similar copper losses in the remaining healthy phases can be obtained. Experimental tests are carried out on a seven-phase permanent magnet synchronous machine (PMSM) with a high total harmonic distortion (THD = 38%) of NS-EMFs. A demonstration video is provided with this paper.

This two-part study proposes a new sensorless control strategy for non-sinusoidal multiphase permanent magnet synchronous machines (PMSMs), especially in integrated motor drives (IMDs). Based on the Sliding Mode Observer (SMO), the proposed sensorless control strategy uses the signals (currents and voltages) of all fictitious machines of the multiphase PMSMs. It can estimate the high-accuracy rotor position that is required in the vector control. This proposed strategy is compared to the conventional sensorless control strategy applying only current and voltage signals of the main fictitious machine, including the fundamental component of back electromotive force (back-EMF) of the non-sinusoidal multiphase PMSMs. Therefore, in order to choose an appropriate sensorless control strategy for the non-sinusoidal multiphase PMSMs, these two sensorless control strategies will be highlighted in terms of precision in the rotor position and speed estimations. Simulation and experimental results of a non-sinusoidal seven-phase PMSM will be shown to verify and compare the two sensorless control strategies. In this part of the study (part I), only the sensorless control in medium and high-speed range is considered. The sensorless control at zero and low-speed range will be treated in the second part of this study (part II).

n experimental proof of concept of a new semi-passive nonlinear piezoelectric shunt absorber, introduced theoretically in a companion article, is presented in this work. This absorber is obtained by connecting, through a piezoelectric transducer, an elastic structure to a resonant circuit that includes a quadratic nonlinearity. This nonlinearity is obtained by including in the circuit a voltage source proportional to the square of the voltage across the piezoelectric transducer, thanks to an analog multiplier circuit. Then, by tuning the electric resonance of the circuit to half the value of one of the resonances of the elastic structure, a two-to-one internal resonance is at hand. As a result, a strong energy transfer occurs from the mechanical mode to be attenuated to the electrical mode of the shunt, leading to two essential features: a nonlinear antiresonance in place of the mechanical resonance and an amplitude saturation. Namely, the amplitude of the elastic structure oscillations at the antiresonance becomes, above a given threshold, independent of the forcing level, contrary to a classical linear resonant shunt. This paper presents the experimental setup, the designed nonlinear shunt circuit and the main experimental results.

Friction reduction using ultrasonic longitudinal surface vibration can modify the user perception of the touched surface and induce the perception of textured materials. In the current paper, the mechanisms of friction reduction using longitudinal vibration are analyzed at different finger exploration velocities and directions over a plate. The development of a non-Coulombic adhesion theory based on experimental results is evaluated as a possible explanation for friction reduction with vibrations that are non-collinear with the finger displacement. Comparison with experimental data shows that the model adequately describes the reduction in friction, although it is less accurate for low finger velocities and depends on motion direction.

Energy management in modular type converters constitutes a key aspect of their operational stability. This paper introduces a full energy management structure for the Extended Overlap-Alternate Arm Converter (EO-AAC) ensuring both equal energy distribution across all six stacks and the maintaining of ripple-free DC current during steady state. The performance of the control structure against active power step events is validated by detailed simulations using EMTP-RV software. Moreover, the full energy management allows the EO-AAC to have an equivalent controllability to Modular Multilevel Converter (MMC) through only two conducting stacks in overlap mode ensuring the power balance. From this observation, it is demonstrated that the use of control strategy like the virtual capacitor to support HVDC system, originally designed for MMC, is possible. Gathering all these controllers leads to a general conclusion which is the dynamic equivalence between EO-AAC and MMC.

This paper proposes a sensorless control strategy based on Sliding Mode Observer (SMO) for a Five-phase Interior Permanent Magnet Synchronous Machine (FIPMSM), with a consideration of the third harmonic component. Compared to conventional three-phase machines, the third harmonic of back electromotive force (back-EMF) contains more information. Thus, in this paper, the first and third harmonic components of the five-phase machine are considered to estimate the rotor position which is necessary for the vector control. Simulation results are shown to verify the feasibility and the robustness of the proposed sensorless control strategy.

More degrees of freedom not only enable multiphase drives to be fault-tolerant but also allow non-sinusoidal electromotive forces (NS-EMFs) in high-quality vector control. NS-EMFs lead to lower costs of design and manufacturing of electrical machines. However, the presence of multi-harmonics in NS-EMFs possibly generates pulsating torque in both healthy and faulty conditions of multiphase drives. To facilitate the use of NS-EMFs, this two-part study proposes control schemes to adaptively improve torque quality of multiphase drives in dealing with multi-harmonics of NS-EMFs. The proposed schemes are based on a simple but effective type of artificial intelligence, Adaptive Linear Neuron (Adaline). The knowledge of multiphase drives including the harmonic ranks of NS-EMFs and the rotor position is exploited to design the online-trained optimal Adalines. The first part of this study is to propose a control scheme using an Adaline for healthy mode with high-quality torque regardless of numerous harmonics in NS-EMFs. The second part of this study introduces a control scheme using another Adaline for open-circuit faults. The proposed schemes are numerically and experimentally validated on a seven-phase permanent magnet synchronous machine (PMSM) possessing a high total harmonic distortion (THD=38%) of NS-EMFs. A demonstration video is provided with this paper.

Conceiving planar magnetic components for power electronic converters is very constraining, especially in the case of prototype development. Indeed, such making requires skills, specific appliances as well as human time for setting up the machine tools and the fabrication process. With the emergence of Fabrication Laboratory (FabLab), conceiving of planar copper foil prototypes becomes more feasible in a shortened time process for engineers and researchers. This paper presents a methodology and process for conceiving power planar transformers with the help of machines and tools that can be found in the usual FabLab.

The purpose of this study is to investigate, through finite element (FE) simulations, the effect of the demagnetizing field in Epstein characterization of grain-oriented electrical steels. A 3D finite element simulation has been realized to represent the parallel and X-stacking configurations in the Epstein frame. The numerical results have been compared with experimental measures. In a parallel configuration, the measured induction is actually the one in the material, whereas the resulting magnetic field differs from the applied one (in magnitude and angle) due to the shape anisotropy (demagnetizing field). In X-stacking configuration, the resulting magnetic field is close to the applied magnetic field (and then the supposed excitation field in the Epstein frame), whereas the magnetic induction has deviated from the axis of the strips.

The modeling of the capacitive phenomena, including the inductive effects becomes critical, especially in the case of a power converter with high switching frequencies, supplying an electrical device. At a low frequency, the electro-quasistatic (EQS) model is widely used to study the coupled resistive-capacitive effects, while the magneto-quasistatic (MQS) model is used to describe the coupled resistive-inductive effects. When the frequency increases, the Darwin model is preferred, which is able to capture the coupled resistive-capacitive-inductive effects by neglecting the radiation effects. In this work, we are interested in specifying the limits of these models, by investigating the influence of the frequency on the electromagnetic field distributions and the impedance of electromagnetic devices. Two different examples are carried out. For the first one, to validate the Darwin model, the measurement results are provided for comparison with the simulation results, which shows a good agreement. For the second one, the simulation results from three different models are compared, for both the local field distributions and the global impedances. It is shown that the EQS model can be used as an indicator to know at which frequency the Darwin model should be applied.

In response to the climate emergency, new uses are plugged to low voltage (LV) electrical networks. The development of self-consumption complicates the LV grid operation, and force distribution system operators (DSOs) to better model and characterize their networks. DSOs mainly use a three-conductor model (3 CM) to compute power flows, and consider error margins of 2% for voltage profiles to reflect their model inaccuracy. The characteristics of the future LV grids call into question these margins, and the models used. In this paper, a four-conductor model (4 CM), and an additional model named 4 CMext, that considers external parameters (i.e., cable temperature, ground electrical resistivity, and value/number of the earthing resistances) are proposed. The best model for cable characterization and voltage profile calculation is chosen; the 4 CMext is more adapted for the characterization, and corresponds with the finite element model, with an error margin of 4%, experimental measurements of 15%, and French cable manufacturer data of 0.5%. For the voltage profile, the 4 CMext provides a more detailed view of the critical cases that could lead to a violation of the limits of the EN 50160 standard than 3 CM and 4 CM. Violations of high or low voltages are underestimated by two to six times by the 3 CM and 4 CM. Not considering external parameters can lead to a voltage profile error of above 3%. In this paper, we recommend that DSOs use the 4 CMext to represent LV networks, which would allow LV networks to be used closer to their physical limits, and avoid or postpone network reinforcements.

During electrical machine manufacturing, the process may induce plastic mechanical strains, especially in the magnetic core. However, magnetic properties are highly sensitive to the material mechanical state. Thus, the performances of electrical machines, which also rely on the magnetic material properties, are often deteriorated. This paper proposes an approach to reduce the impact of the forming process on the magnetic core performances by creating high localized heterogeneous deformations instead of having a low homogeneous deformation distributed on the whole structure. A NO (non-oriented) FeSi (1.3%) electrical steel (M330-35A) is characterized after uniaxial tensile test. Samples are deformed either in heterogeneous or in homogeneous ways while keeping the same global deformation. Experimental measurements show that, for the same displacement value, the heterogeneous configuration, with localized strain, deteriorates less the global magnetic properties than the homogeneous configuration. These results are supported by a magneto-mechanical modeling approach that predicts accurately the physical behavior of test samples.

In this paper, it is identified that unstable weak grid connection of voltage source inverters (VSIs) is dominantly caused by the current control. In particular, it is found the proportional gain k p of conventional PI controller cannot balance the grid voltage impact and damping capability when a weak grid with short circuit ratio (SCR) < 1.3 is connected. This issue is solved in this paper by simply restructuring the PI controller as an IP controller for current control. This IP controller will not change the tuning method of current control and make this VSI indeed connect to a very weak grid with rated power injection.

This paper deals with the experimental investigation of the effect of impregnation process on the normal magnetization curve and iron losses of electrical steels. To address this issue, several laminated toroidal magnetic circuits have been designed to characterize the magnetic properties with the flux metric method. The first configuration considers magnetic circuits wrapped with adhesive tape so that the dielectric resin will be deposited only on the outer surface of the magnetic circuit. In the second configuration, the magnetic circuits are unwrapped, which will allow the resin to diffuse within the inter-laminar spaces of the magnetic circuit. The obtained experimental results show significant effects on the magnetic properties in both cases. However, depending on the considered configuration, the resin diffusion also has an influence on the changes in magnetic properties.

The design and closed loop control of a device able to produce both longitudinal mode and transverse mode vibration, at about the same resonance frequency (60 kHz) are presented in this article. The structure uses an array of piezo-ceramics. A dynamic analysis is performed on the obtained modes, and their dynamic lumped parameters are identified. A closed loop control is performed to maintain the desired vibration amplitude in the presence of a finger. Longitudinal and transverse motion cartographies show that the objective of achieving and controlling pure modes independently has been achieved. Using this device, tribological, psychophysical and energetic analyses are carried out. The analyses show that in terms of friction measurements and perception, both modes produce equivalent results. In terms of active power losses, an advantage of the longitudinal mode over the transverse mode is observed due to the interaction with the finger.

One way to enhance the performance of vibration control with piezoelectric shunt is to use a negative capacitance in the shunt circuit. This component is very effective and pro- vides good results in terms of attenuation improvement without significantly increasing the complexity of the shunt network. However, negative capacitances are built using oper- ational amplifiers and, in some applications, the risk of saturation of the outputs of the operational amplifier exists. This constitutes a non-negligible aspect since it leads to a non-proper functioning of the control system which significantly deteriorates the control performance or even triggers instability phenomena. In light of this limitation, this paper proposes strategies to decrease the outputs of the operational amplifier in order to reduce the risk of saturation acting just on the values of the circuit components, without worsen- ing the attenuation performance. However, when the achievable reduction is not sufficient, it is also possible to act on other components accepting a deterioration of the attenuation performance. Guidelines are provided for properly choosing the best shunt circuit configu- ration accounting for both the extent of the operational amplifier outputs and the control performance. The paper also evidences that the mechanical part of the system cannot be neglected in the analysis when assessing the operational amplifier outputs. Furthermore, two different circuit types used to build the negative capacitance are compared in terms of output requirements. This analysis shows that there is no circuit always less demanding than the other and that the choice of the circuit is not always straightforward. Therefore, a multi-degree of freedom model is presented, which is essential to understand which con- figuration of the negative capacitance has to be used in a given engineering application. All the presented outcomes are validated through an experimental campaign.

This paper presents a general operational planning framework for controllable generators, one day ahead, under uncertain re-newable energy generation. The effect of photovoltaic (PV) power generation uncertainty on operating decisions is examined by incorporating expected possible uncertainties into a two-stage unit commitment optimization. The planning objective consists in minimizing operating costs and/or equivalent carbon dioxide (CO 2 ) emissions. Based on distributions of forecasting errors of the net demand, a LOLP-based risk assessment method is proposed to determine an appropriate amount of operating reserve (OR) for each time step of the next day. Then, in a first stage, a deterministic optimization within a mixed-integer linear programming (MILP) method generates the unit commitment of controllable generators with the day-ahead PV and load demand prediction and the prescribed OR requirement. In a second stage, possible future forecasting uncertainties are considered. Hence, a stochastic operational planning is optimized in order to commit enough flexible generators to handle unexpected deviations from predic-tions. The proposed methodology is implemented for a local energy community. Results regarding the available operating reserve, operating costs and CO2 emissions are established and compared. About 15% of economic operating costs and environmental costs are saved, compared to a deterministic generation planning while ensuring the targeted security level.

This paper presents a novel method for demagnetization fault detection in permanent magnet synchronous machine (PMSM). Demagnetization fault is a common problem existing in PMSM which deteriorates the machine performance and can lead to serious subsequential machine damages. Unlike the most popular method based on the analysis of the machine currents for detecting this type of fault, the approach proposed in this paper analyzes the voltage signal of a non-invasive search coil by means of Hilbert Huang transform. Simulations are carried out with a two dimensional finite element analysis (FEA) for different demagnetization levels to test the capability of the proposed method to detect PM demagnetization faults.

To face environmental issues, SNCF, the French railway, has chosen to improve the energy efficiency of its electrical power system by investigating solutions for regenerative braking. With the contribution of Railenium, a research and test center in railway activities, they aim to recover the braking energy by setting up a reversible inverter in a DC substation “Masséna”. The issue is to test, implement and compare various control solutions to increase the energy efficiency with minimum impacts on the railway operation. In this paper, a simulation model for studying a reversible power substation is addressed by considering AC and DC equivalent electrical sources. The proposed model provides a reliable tool for analyzing the behavior of the railway electrical network during specially braking mode. In order to validate this model, its simulation results are compared with the ones obtained from Esmeralda, the SNCF professional software. A first configuration is led without the inverter and gives certified Esmeralda results and validates the proposed model despite some gaps in powers and voltages due to differences in input data and models. A second comparison with inverter is presented to highlight the main difference between the proposed model and Esmeralda. In addition, laboratory experimental activities are put forward to investigate the proposed model by using power-hardware-in-the-loop simulations. Finally, a simulation test under MATLAB software with fifty train’s traffic is presented to estimate the energy saving thanks to the installed inverter. For this latter case study, the system sent back to the national AC grid around 6.9% of the total energy consumed by all trains.

This paper shows the influence of the shift phase angle ψ between phase currents and back-electromotive forces on magnetic radial forces and torque ripple for a specific low power permanent magnet synchronous machine. This influence is firstly demonstrated through analytical development considering only the first harmonic values. Then, magnetic pressure harmonics versus space and frequency as well as torque ripple are evaluated on the studied motor for different angles using finite element approach. The aim is to establish a good compromise between consumed current, torque and radial force harmonics at the origin of the electromagnetic noise. Experimental measurements with a sensorless field-oriented control are detailed.

In this paper, the vector extension of the Jiles-Atherton hysteresis model is modified to predict both alternating and rotational field strength variations observed in a nonoriented silicon steel sheet. The model parameters are changed to be functions of the magnitude and direction of flux density, and the anhysteretic magnetic characteristics are identified from several unidirectional alternating measurements. We demonstrate that the modified vector Jiles-Atherton model can predict both alternating and rotational field strength variations with better accuracy than the “basic” approach.

In this paper, the magnetic ageing of a bulk forged non-annealed magnetic core, used in claw pole synchronous machine, is investigated. The study is carried out by characterizing the material properties of two groups of samples subjected to a thermal ageing at 180 °C that corresponds to the maximum operating temperature of the claw pole rotor. The investigated characteristics are the electrical conductivity, the magnetic properties, the material microstructure and the Vickers hardness. They were characterized along with the ageing time. The results show that, during the thermal ageing, the hysteresis losses and the Vickers hardness have been affected by the magnetic ageing, whereas the electric conductivity and the normal B-H curve have not been modified. The microstructure analyses showed that carbides precipitates were the main cause behind the magnetic ageing. Moreover, the comparison between the results of two groups of samples revealed the possibility that the magnetic ageing of the material could have started during the manufacturing process of the magnetic core.

Deep learning (DL) has attracted more and more attention in computational electromagnetism. Particularly, the Convolutional Neural Network (CNN) is one of the most popular learning models in DL due to its excellent capacity for feature extraction and convergence. The efficiency of CNN mainly depends on how many training samples are needed to effectively converge the network. The sample preparation process often involves a lot of numerical computations, which can be very expensive and time-consuming. In this paper, based on the traditional DL network training procedure, two different approaches, namely adding smart training samples and reference samples, are proposed to help the DL network converge. The smart sample selection is based on a greedy algorithm, which can be applied for both training and reference samples. The influences of these two approaches on the CNN training process are investigated by an example of the coupled magneto-thermal computation applied to a transformer. Numerical results show that the two proposed approaches can significantly help the network to converge and improve the efficiency of the DL model.

In this paper, a novel five-phase fractional-slot concentrated winding (FSCW) with 20-slot/22-pole is presented. It benefits not only the advantages of conventional FSCW, but also weak space harmonics of magnetomotive force (mmf). The winding allows eliminating the 1st sub-order harmonic. The new layout of the winding topology is obtained by a combination of stator shift technique of the winding in the slots with a special coupling of the windings (star-pentagon), using winding function theory. The high performances of the new winding layout are validated using finite element method (FEM). Compared to the conventional winding, the winding factor and the THD of mmf are improved by 1.3% and 2.2%, respectively. With the same injection of current density, the average output torque is increased by 1% and the torque ripple is decreased by 60%. The eddy current losses in the PMs at rated speed (600 rpm) and 2100 rpm speed are improved by 67% and 56%, respectively.

The quality of a local physical quantity obtained by the numerical method such as the finite element method (FEM) attracts more and more attention in computational electromagnetism. Inspired by the idea of goal-oriented error estimate given for the Laplace problem, this work is devoted to a guaranteed a posteriori error estimate adapted for the quantity of interest (QOI) linked to magnetostatic problems, in particular, to the value of the magnetic flux density. The development is principally based on an equilibrated flux construction, which ensures fully computable estimators without any unknown constant. The main steps of the mathematical development are given in detail with the physical interpretation. An academic example using an analytical solution is considered to illustrate the performance of the approach, and a discussion about different aspects related to the practical point of view is proposed.

In time domain electromagnetic field problems that have a fast time response with sharp field change or need a long time transient process to get the steady-state solution, a large number of time step iterations are required using the classical time-stepping method. A reduced model based on Sinc interpolation is proposed in this work. The accuracy of the proposed method does not depend on the traditional time-domain discretization step but only the number of sampling points. Two numerical examples, namely an electro-quasistatic problem and a field-circuit coupled problem, are considered to illustrate the accuracy and performance of the proposed method. It is shown that only a few pre-computed samplings are sufficient to obtain a good performance in comparing with the traditional time-stepping method.

Abstract In electrical systems, the main objective is to satisfy the load demand at the least cost without having imbalance between generation and consumption. Thus, the uncertainty of photovoltaic (PV) power production must be considered in generation planning. In this paper, the optimal generation scheduling in an urban microgrid is made by taking in consideration operating reserve (OR) provision and under stochastic characteristics of PV power prediction. By considering a prescribed risk level of unbalancing, a dynamic programming (DP) algorithm sets the operational planning of conventional generators, so that the operational cost and available operating reserve can be calculated. Then, the effect of PV power uncertainty into the unit commitment is analysed by considering PV forecast intervals with a 95 % confidence level. The unit commitment is then recalculated with new generator set points and the same criteria. Finally, variations of the targeted minimized costs and obtained OR is analysed according to the considered uncertainty.

One of the main technological stumbling blocks in the field of environmentally friendly vehicles is related to the energy storage system. It is in this regard that car manufacturers are mobilizing to improve battery technologies and to accurately predict their behavior. The work proposed in this paper deals with the advanced electro-thermal modeling of a hybrid energy storage system integrating Lithium-ion batteries and supercapacitors. The objective is to allow the aging aspects of the components of this system to be taken into account. The development of a model including the electro-thermal behaviors makes it possible to evaluate the progressive degradation of the performance of the hybrid energy storage system. The characterization of both components constituting the hybrid system is carried out via a hybrid Particle Swarm–Nelder–Mead (PSO–NM) optimization algorithm using the experimental data of an urban electric vehicle. The obtained results show the good performance of the developed model and confirm the feasibility of our approach. The use of the PSO–NM optimization algorithm facilitated the identification of the parameters of the developed model with high efficiency, as the error observed is less than 3%. The advanced model associated with an adapted sizing method can be used in many cases to compare energy management strategies in electric vehicle applications.

16MnCr5 steel parts were additively manufactured by laser powder bed fusion in order to investigate the effect of microstructure on electromagnetic properties. As process parameters have a direct impact on the obtained microstructure, different conditions were used to manufacture samples on which magnetic and electrical tests were conducted. The obtained results were presented and discussed in terms of density, microstructure and electromagnetic properties. Finally, correlations have been demonstrated between the microstructure and the electromagnetic performances. Lower magnetic and electric properties were obtained with the higher porosity rates at low volume energy density. The microstructural effects were evidenced, through a decrease in magnetic properties with grain orientation, and an improvement with stress relief annealing.

The increasing development of storage systems connected to electrical networks is stimulated by network management issues related to recent energetic landscape evolutions such as the increasing integration of renewable production sources. Hydro-pneumatic systems seem to offer a clean and cheap energy storage solution among the set of existing storage techniques. The present study analyses an air–water direct contact accumulation system, in closed cycle, using a rotodynamic reversible pump/turbine. The use of a unique energy conversion machine and easy-to-recycle materials could lead to cost-effective, environmentally friendly storage technique with long service life. The paper is focused on the experimental implementation and analysis of the system in a Lab environment, and the modeling of its multi-physic dynamic behavior. To deal with the variable operating conditions of the system, two different real time control strategies of the hydraulic machine were successfully tested. Finally, the global system efficiency is discussed. The efficiency control strategy was achieved with a 31% round trip efficiency and the power control strategy lead to 5% and 23% precision on exchanged power in charge and discharge modes respectively. The multi-physic dynamic model led to a 4% error of turbine mode acceleration prediction showing the interest of such a modeling method for such transient systems.

The forces that are developed when manipulating objects generate sensory cues that inform the central nervous system about the qualities of the object's surface and the status of the hand/object interaction. Afferent responses to frictional transients or slips have been studied in the context of lifting/holding tasks. Here, we used microneurography and an innovative tactile stimulator, the Stimtac, to modulate both the friction level of a surface, without changing the surface or adding a lubricant, and, to generate the frictional transients in a pure and net fashion. In three protocols, we manipulated: the frictional transients, the friction levels, the rise times, the alternation of phases of decrease or increase in friction to emulate grating-like stimuli. Afferent responses were recorded in 2 FAIs, 1 FAII, 2 SAIs and 3 SAIIs from the median nerve of human participants. Independently of the unit type, we observed that: single spikes were generated time-locked to the frictional transients, and that reducing the friction level reduced the number of spikes during the stable phase of the stimulation. Our results suggest that those frictional cues are encoded in all the unit types and emphasize the possibility to use the Stimtac device to control mechanoreceptor firing with high temporal precision.

Low voltage distribution networks have not been traditionally designed to accommodate the large-scale integration of decentralized photovoltaic (PV) generations. The bidirectional power flows in existing networks resulting from the load demand and PV generation changes as well as the influence of ambient temperature led to voltage variations and increased the leakage current through the cable insulation. In this paper, a machine learning-based framework is implemented for the identification of cable degradation by using data from deployed smart meter (SM) measurements. Nodal voltage variations are supposed to be related to cable conditions (reduction of cable insulation thickness due to insulation wear) and to client net demand changes. Various machine learning techniques are applied for classification of nodal voltages according to the cable insulation conditions. Once trained according to the comprehensive generated datasets, the implemented techniques can classify new network operating points into a healthy or degraded cable condition with high accuracy in their predictions. The simulation results reveal that logistic regression and decision tree algorithms lead to a better prediction (with a 97.9% and 99.9% accuracy, respectively) result than the k-nearest neighbors (which reach only 76.7%). The proposed framework offers promising perspectives for the early identification of LV cable conditions by using SM measurements.

The development of local energy communities and collective self-consumption framework at a large scale requires new control methods that take into account users preferences. This article presents a model of such a community, with diverse actors (photovoltaic generators, electric vehicles, storage system and tertiary buildings). Game theory is used to model the preferences of each user and to build a mathematical framework where each user optimizes individually his power profile according to these preferences. An ADMM distributed algorithm (Alternating Direction of Method of Multipliers) is employed for practical implementation. Thus, a central agent is no longer needed to reach the system equilibrium, in which all users are satisfied while ensuring that the local energy community does not import more power from the grid than allowed. The simulations performed on real data for different scenarios representing diverse users behaviors show that the developed approach converges to a stable state, and leads to a maximization of local energy exchanges.

In order to model GaN-HEMT switching transients and determine power losses, a compact model including dynamic RDSon effect is proposed herein. The model includes mathematical equations to represent device static and capacitance-voltage characteristics, and a behavioural voltage source, which includes multiple RC units to represent different time constants for trapping and detrapping effect from 100 ns to 100 s range. All the required parameters in the model can be obtained by fitting method using a datasheet or experimental characterisation results. The model is then implemented into our developed virtual prototyping software, where the device compact model is co-simulated with a parasitic inductance physical model to obtain the switching waveform. As model order reduction is applied in our software to resolve physical model, the device switching current and voltage waveform can be obtained in the range of minutes. By comparison with experimental measurements, the model is validated to accurately represent device switching transients as well as their spectrum in frequency domain until 100 MHz. In terms of dynamic RDSon value, the mismatch between the model and experimental results is within 10% under different power converter operation conditions in terms of switching frequencies and duty cycles, so designers can use this model to accurately obtain GaN-HEMT power losses due to trapping and detrapping effects for power electronics converters

This paper presents a diagnostic method of inverter open-switch and open-phase faults in multiphase PMSM drives. Adequate variables called “Virtual Current Vectors (VCVn)” are firstly defined. The projection of the zero-sequence current component (ZSCC) on these variables was used to define two simple fault indices. High sensitivity to fault is thus induced but with a good robustness to transient states and variation of machine parameters. The mathematical development of the proposed method is provided and supported by experimental tests conducted on two prototypes of multiphase machines in the laboratory, sinusoidal and bi-harmonic PMSMs. The experimental results confirm the effectiveness and the robustness of the proposed method and its capability to detect the single and multiple open-switches and open-phase faults in the electric drive.

Simulation is a key step during the development of energy management strategies (EMSs) for hybrid electric vehicles (HEVs). Moreover, optimal algorithms such as dynamic programming (DP) are used off‐line to define a benchmark for real‐time EMSs. However, several assumptions are made on the model to determine the appropriate energy management of an HEV. The rotating masses of the mechanical transmission, which are related to the vehicle dynamics, are often neglected for EMS development. In this study, different models for the EMS design of a parallel HEV are compared. An EMS based on the dynamical model that considers the rotating masses is used as a benchmark. A static model considering only the static mass of the vehicle is also studied. Intermediate models, such as an average gear model and an average mass model, are also considered. Simulations are performed using different driving cycles. The comparisons are based on the fuel consumption and also the computation time resulting from EMSs derived from the different models. Globally, the static model leads to an average error up to 20% on the energy consumption in comparison with the dynamical model. The average mass model leads to an error less than 1%. For real‐time simulations, the average mass model allows to reduce the computation time by a factor of 10 in comparison with the dynamical model.

Due to the high switching speed of Gallium Nitride (GaN) transistors, parasitic inductances have significant impacts on power losses and electromagnetic interferences (EMI) in GaN-based power converters. Thus, the proper design of high-frequency converters in a simulation tool requires accurate electromagnetic (EM) modeling of the commutation loops. This work proposes an EM modeling of the parasitic inductance of a GaN-based commutation cell on a printed circuit board
(PCB) using Advanced Design System (ADS®) software. Two different PCB designs of the commutation loop, lateral (single-sided) and vertical (double-sided) are characterized in terms of parasitic inductance contribution. An experimental approach based on S-parameters, the Cold FET technique and a specific calibration procedure is developed to obtain reference values for comparison with the proposed models. First, lateral and vertical PCB loop inductances are extracted. Then, the whole
commutation loop inductances including the packaging of the GaN transistors are determined by developing an EM model of the device’s internal parasitic. The switching waveforms of the GaN transistors in a 1 MHz DC/DC converter are given for the different commutation loop designs.
Finally, a discussion is proposed on the presented results and the development of advanced tools for high-frequency GaN-based power electronics design.

The increasing importance of cascaded multilevel converters (CMCs), and the sub-category of modular multilevel converters (MMCs), is illustrated by their wide use in high voltage DC connections and in static compensators. Research is being undertaken into the use of these complex pieces of hardware and software for a variety of grid support services, on top of fundamental frequency power injection, requiring improved control for non-traditional duties. To validate these results, small-scale laboratory hardware prototypes are often required. Such systems have been built by many research teams around the globe and are also increasingly commercially available. Few publications go into detail on the construction options for
prototype CMCs, and there is a lack of information on both design considerations and lessons learned from the build process, which will hinder research and the best application of these important units. This paper reviews options, gives key examples from leading research teams, and summarizes knowledge gained in the development of test rigs to clarify design considerations when constructing laboratory-scale CMCs.

The paper deals with electro-thermal modeling lithium-ion batteries. The model computes losses distrubution distribution to allow an accurate temperature distribution. The electrical model is updated through the mean temperature of the battery to insure an accurate estimation of losses at any temperature.
The obtained results show that the proposed model is able to simulate the dynamic interaction between the electric and the thermal battery behavior, and high performance for the cell surface temperature prediction.

Combining multisensory sources is crucial to interact with our environment, especially for older people who are facing sensory declines. Here, we examined the influence of textured sounds on haptic exploration of artificial textures in healthy younger and older adults by combining a tactile device (ultrasonic display) with synthetized textured sounds. Participants had to discriminate simulated textures with their right index while they were distracted by three disturbing, more or less textured sounds. These sounds were presented as a real-time auditory feedback based on finger movement sonification and thus gave the sensation that the sounds were produced by the haptic exploration. Finger movement velocity increased across both groups in presence of textured sounds (Rubbing or Squeaking) compared to a non-textured (Neutral) sound. While young adults had the same discrimination threshold, regardless of the sound added, the older adults were more disturbed by the presence of the textured sounds with respect to the Neutral sound. Overall, these findings suggest that irrelevant auditory information was taken into account by all participants, but was appropriately segregated from tactile information by young adults. Older adults failed to segregate auditory information, supporting the hypothesis of general facilitation of multisensory integration with aging.

This paper presents an evolution of control systems of Modular Multilevel Converters (MMCs) focusing on the internal voltages and currents dynamics. MMCs have passive components that create extra dynamics compared to conventional VSCs. Some control schemes that do not consider these internal dynamics may still stabilize the system asymptotically thanks to the linearisation in the modulation step. However these control schemes are less robust because they are prone to poor damped oscillations on the dc side of the converter. The MMC circuit and energy relationships are presented in this paper. Along with a gradual development of the energy based control, the important roles of each internal dynamics are clearly demonstrated. Experimental results are presented to show the impacts of the linearisation in the modulation step on the system behaviour.

Decision-making is a crucial and difficult step in the design process of complex systems such as the hybrid powertrain. Finding an optimal solution requires the system feedback. This can be, depending on the granularity of the models at the component level, highly time-consuming. This is even more true when the system’s performance is determined by its control. In fact, various possibilities can be selected to deliver the required torque to the wheels during a driving cycle. In this work, two different design strategies are proposed to minimize the fuel consumption and the cost of the hybrid powertrain. Both strategies adopt the iterative framework which allows for the separation of the powertrain design problem and its control while leading to system optimality. The first approach is based on model reduction, while the second approach relies on improved cycle reduction techniques. They are then applied to a parallel hybrid vehicle case study, leading to important cost reduction in reasonable delays and are compared using different metrics.

When a finger touches an ultrasonic vibrating plate, a non-sinusoidal contact force is produced. This force is called acoustic finger force. In a setup where closed-loop control is performed on the vibration amplitude, a component of the acoustic finger force can be measured at the fundamental vibration frequency of the plate. This calculation is obtained from the measurement of the variation of the controller voltage between the no-load case and when a finger is present. This calculation is made for a group of twelve participants. From these results a PCA (Principal Component Analysis) model is created. This model permits estimation of the acoustic finger force response of a participant at any vibration amplitude, based on a one or two point measurement. Finally, a linear relation between the PCA coefficients and the friction reduction is proposed. The objective of this relation would be to ultimately provide the means to create an amplitude reference calibration based on the desired friction reduction level, and thus be able to produce a standardized tactile feedback for each user, despite the biomechanical differences in finger pad properties between subjects.

This article proposes a novel mean for tuning the natural frequency of an electromagnetic resonant shunt, using a pulse-width modulation (PWM) circuit. It is used to modulate the value of the capacitance of the shunt, and the electrical frequency is shown to be proportional to the command parameter of the PWM, the duty cycle. An easy and efficient strategy to tune the resonant shunt in real time is then proposed, thus obtaining a low powered and always stable vibration control device. The article proposes the theory of PWM, giving a robust method to predict the dynamics of the system. Then, an accurate multi-mode theoretical model of the tunable resonant shunt coupled to an elastic structure is proposed and experimentally validated on an elastic multi-mode structure, in the case of two different control strategies. The first one is a standard resonant shunt with both the electrical frequency and damping optimized to reduce a given resonance peak. The second one is based on a resonant shunt with the electrical damping as low as possible, which creates an antiresonance and a “notch” type mechanical response at the driving frequency. Both strategies are experimentally validated with real time variation and adaptation of the electrical frequency, obtaining an efficient vibration control device, able to reduce by a factor 40 the vibration level.

The new power GaN transistors allow to increase the operating frequency of converters to megahertz range, thanks to their low switching time that is of a few nanoseconds or less. This permits to reduce the values and the volume of the passive components, and enhance the power density of power converters. However, inductors needed for energy storage still take a large volume in converters compared with the others components, because of their weak energy density. Further, high frequency operation require low-losses magnetic materials. In this paper, a design method of PCB inductors is proposed. A flexible ferrite sheet is used to enhance the inductance value and ease the realization of custom-shape devices. The design method of the inductor is based on the optimization of the inductor volume taking into account thermal issues of the magnetic sheets. Also a simulation method is proposed to calculate the equivalent stray capacitance of the inductors. The proposed method provides a losses-volume trade-off that helps designers to optimize the inductor for their application.

The paper investigates the management of drain voltage and current slew rates (i.e., dv/dt and di/dt) of high-speed GaN-based power switches during the transitions. An active gate voltage control (AGVC) is considered for improving the safe operation of a switching cell. In an application of open-loop AGVC, the switching speeds vary significantly with the operating point of the GaN HEMT on either or both current and temperature. A closed-loop AGVC is proposed to operate the switches at a constant speed over different operating points. In order to evaluate the reduction in the electromagnetic disturbances, the common mode currents in the system were compared using the active and a standard gate voltage control (SGVC). The closed-loop analysis carried out in this paper has shown that discrete component-based design can introduce limitations to fully resolve the problem of high switching speeds. To ensure effective control of the switching operations, a response time fewer than 10 ns is required for this uncomplex closed-loop technique despite an increase in switching losses.

In order to have a better convergence and accuracy for solving the ion-flow field problem, a novel and general numerical approach is proposed. In the past, the framework of the traditional mesh based method has a dilemma that the Kapzov boundary condition can be imposed properly, and it must have two loops: the “well-posed” problem is solved in the inner loop and the secant based method is applied to impose the Kapzov assumption in the outer loop. In contrast, the proposed method solves the ion flow field problem from the perspective of the inverse problem. The original boundary value problem is transformed into a regularized optimization problem based on the priori information about the smooth ion distribution on the conductors. The objective function is separated into two parts and minimized by the alternating direction iterative method. In contrast to the traditional methods, the proposed method has removed the redundant iterations and the contentious simplifications. Numerical experiments show that the performance of the proposed method is superior to the traditional method and the results obtained by the proposed method agree better with the physical law than the traditional method.

DOI: 10.1109/TVT.2020.3047219

Metamodels proved to be a very efficient strategy for optimizing expensive black-box models, e.g., Finite Element simulation for electromagnetic devices. It enables the reduction of the computational burden for optimization purposes. However, the conventional approach of using metamodels presents limitations such as the cost of metamodel fitting and infill criteria problem-solving. This paper proposes a new algorithm that combines metamodels with a branch and bound (B&B) strategy. However, the efficiency of the B&B algorithm relies on the estimation of the bounds; therefore, we investigated the prediction error given by metamodels to predict the bounds. This combination leads to high fidelity global solutions. We propose a comparison protocol to assess the approach’s performances with respect to those of other algorithms of different categories. Then, two electromagnetic optimization benchmarks are treated. This paper gives practical insights into algorithms that can be used when optimizing electromagnetic devices.

D. Fu, J. Gong, Y. Xu, F. Gillon and N. Bracikowski, "Coupled Circuit and Magnetic Model for a Transverse Flux Permanent Magnet Linear Motor," in IEEE Access, vol. 8, pp. 159274-159283, 2020, doi: 10.1109/ACCESS.2020.3020258.
Abstract: In this paper, a strong coupling between magnetic and electric phenomena is provided allowing to have an accurate and high-speed coupled model. A coupled circuit and magnetic model for an E-core transverse flux permanent magnet linear motor (TFPMLM) is proposed, which has an advantage linked to reducing time computing more than ten times when compared to 3-D finite-element model (FEM). Firstly, a multi-plane flexible-mesh nonlinear equivalent magnetic network (EMN) model is proposed to improve the computation efficiency as well as the high precision of the magnetic model. And a new method to define the converged iterative process is presented to further decrease the computing time. Secondly, the magnetic circuit and electric circuit are normalized into a solution matrix by introducing controlled sources and discretization methods which forms the coupled model. Then, the magnetic flux in the magnetic circuits and the current in the electric circuits are obtained simultaneously for each time step. The characteristics such as the air-gap flux density distribution, output thrust force waveforms and the phase currents are analyzed by the proposed coupled model. The modeling approach is approved by comparison with the 3-D FEM model. Finally, the proposed model is validated through the experimental setup with the machine prototype.
keywords: {couplings;finite element analysis;iterative methods;linear motors;magnetic circuits;magnetic flux;permanent magnet motors;iterative process;computation efficiency;EMN model;TFPMLM;coupling;flexible-mesh nonlinear equivalent magnetic network model;3-D finite-element model;E-core transverse flux permanent magnet linear motor;high-speed coupled model;electric phenomena;magnetic phenomena;coupled circuit;electric circuit;magnetic circuit;Integrated circuit modeling;Magnetic circuits;Magnetic flux;Atmospheric modeling;Computational modeling;Permanent magnet motors;Solid modeling;Coupled model;electric circuit;equivalent magnetic network (EMN);linear motor;transverse flux},
URL: https://ieeexplore-ieee-org.ressources-electroniques.univ-lille.fr/stamp/stamp.jsp?tp=&arnumber=9180311&isnumber=8948470

Purpose
This paper deals with the study of the influence of the phase shift between currents and back-electromotive forces (back-EMF) on torque ripple and radial magnetic forces for a low power synchronous machine supplied with 120 degrees square-wave currents. This paper aims to establish a good compromise between efficiency, harmonics of torque and harmonics of radial forces at the origin of the electromagnetic noise.

Design/methodology/approach
Based on a finite element approach, torque and magnetic pressure harmonics versus space and frequency are evaluated for different angle values. The evolutions of the different harmonics against the load angle are analyzed and compared to those of experimental measurements.

Findings
Depending on the load torque, field-weakening or field-boosting can be used to reduce current harmonics contributing the most to the radial magnetic forces responsible for the noise. Besides, a compromise can be found to avoid deteriorating too much the performances of the machine, thus being suitable with an industrial application.

Research limitations/implications
This study concerns low power permanent magnet synchronous machines with concentrated windings and driven with a trapezoidal control, while having sinusoidal back-EMF.

Originality/value
The use of a simple mean and suitable with a large-scale manufacturing industry to reduce the identified electromagnetic-borne noise of a specific electric drive makes the originality.

In this paper, the problem of optimal placement of virtual inertia is considered as a techno-economic problem from a frequency stability point of view. First, a data driven-based equivalent model of battery energy storage systems, as seen from the electrical system, is proposed. This experimentally validated model takes advantage of the energy storage system special attributes to contribute to inertial response enhancement, via the virtual inertia concept. Then, a new framework is proposed, which considers the battery storage system features, including annual costs, lifetime and state of charge, into the optimal placement formulation to enhance frequency response with a minimum storage capacity. Two well-known dynamical frequency criteria, the frequency nadir and the rate of change of frequency, are utilized in the optimization formulation to determine minimum energy storage systems. Moreover, a power angle-based stability index is also used to assess the effect of virtual inertia on transient stability. Sensitivity and uncertainty analyses are further conducted to assess the applicability of the method. The efficiency of the proposed framework is demonstrated on a linearized model of a three-area power system as well as two nonlinear systems. Simulation results suggest that the proposed method gives improved results in terms of stability measures and less ESS capacity, when compared with other methods proposed in the literature.

DOI: 10.3390/en13215538

In recent years, analytical tools and approaches to model the costs and benefits
of energy storage have proliferated in parallel with the rapid growth
in the energy storage market. Some analytical tools focus on the technologies
themselves, with methods for projecting future energy storage technology
costs and different cost metrics used to compare storage system designs.
Other tools focus on the integration of storage into larger energy systems,
including how to economically operate energy storage, estimate the air pollution
and greenhouse gas emissions effects of storage, or understand how
policy and market rules influence storage deployment and operation. Given
the confluence of evolving technologies, policies, and systems, we highlight
some key challenges for future energy storage models, including the use of
imperfect information to make dispatch decisions for energy-limited storage
technologies and estimating how different market structures will impact the
deployment of additional energy storage.

This study is interested in optimisation of both sizing and energy management system of a hybrid storage system (HSS) associated with photovoltaic panels. The battery (BT) considered as the principal storage organ and a super-capacitor used as the secondary storage system to improve the BT life span makes up the HSS. The main purpose of this study is to explore a novel optimisation approach to jointly optimise the sizing and the fuzzy logic energy management system (FLEMS). In fact, an optimisation function based on sequential quadratic programming algorithm is proposed. The optimisation methodology has been performed jointly and successfully for the sizing of the BT storage system and the membership functions parameters
of the FLEMS in order to decrease the levelised cost of energy with a violation time by 5% of mean absolute percentage error
score <1.5% throughout the year. According to the simulations results, a benefit analysis has been done to assess the associated financial impact.

Despite their low environmental impact, electrical vehicles have low penetration in the automotive market. Consumers are reluctant for technical reasons (limited driving range and long charging time) but also for an economic reason (high investment costs). Electric vehicle total cost of ownership (TCO) is often perceived as higher than for a thermal car, especially in Europe where diesel cars have a lower TCO than gasoline cars. Accurate TCO estimations are critical, but most of the techno-economic studies of electrified vehicles are based on very simplified energy models. In this paper, a techno-economic model is developed using an accurate technical model of an electric vehicle and a diesel car of the same segment. These technical models are validated by experimental measurements on real cars using real driving cycles. These models are then coupled to economic models to calculate TCO for a French case study. The total cost of ownership of the studied electric car is lower than for the equivalent diesel car by about 1000€ for a 5-year ownership period. Of particular importance is the finding that using real driving cycles instead of standard driving cycles decreases the TCO of electric cars while simultaneously increasing the TCO of diesel vehicles. This has implications for techno-economic models, suggesting that the typical TCO approach that uses manufacturer-reported standard cycle data may be systemically biased towards thermal vehicles. In order to understand how TCO may change in different locations, a sensitivity analysis varies different technical and economic factors. Government subsidy, ownership duration, and vehicle depreciation are the most important factors for the TCO of electric vehicles. However, TCO of the electric cars can be lower than the TCO of equivalent diesel cars under a wide range of reasonable inputs.

INTRODUCTION: This paper presents a distributed approach to optimise self-consumption on a local energy community containing photovoltaic generators, electric vehicles, loads and a storage system.
OBJECTIVES: The goal is to maximise energy sharing between users while preserving the indivual objectives of each user.
METHODS: Game theory is employed to model users’ behavior and preferences. A distributed algorithm is used to solve the optimisation problem. In addition, a physical model of the grid is built to verify if the solutions respect grid constraints. Finally, a private blockchain environnement is deployed to concretely implement this distributed framework with a smart contract.
RESULTS: It is shown that the proposed approach effectively leads to an increase of self-consumption rate on the local grid.
CONCLUSION: The proposed distributed framework, combining game theory and blockchain, shows real potential to improve energy sharing on energy communities.

Piezoelectric devices with integrated actuation and sensing capabilities are often used for the development of electromechanical systems. The present paper addresses experimentally the nonlinear dynamics of a fully integrated circular piezoelectric thin structure, with piezoelectric patches used for actuationand other for sensing. A phase-locked loop control system is used to measure the resonant periodic response of the system under harmonic forcing, in both its stable and unstable parts. The single-mode response around a symmetric resonance as well as the coupled response around an asymmetric resonance, involving two companion modes in 1:1 internal resonance, is accurately measured. For the latter, a particular location of the patches and additional signal processing is proposed to spatially discriminate the response of each companion mode. In addition to a hardening behavior associated with geometric nonlinearities of the plate, a softening behavior predominant at low actuation amplitudes is observed, resulting from the material piezoelectric nonlinearities.

Because of trapped charges in GaN transistor structure, device dynamic ON-state resistance RDSon is increased when it is operated in high frequency switched power converters, in which device is possibly operated by zero voltage switching (ZVS) to reduce its turn-ON switching losses. When GaN transistor finishes ZVS during one switching period, device has been operated under both reverse and forward conduction. Therefore its dynamic RDSon under both conduction modes needs to be carefully measured to understand device power losses. For this reason, a measurement circuit with simple structure and fast dynamic response is proposed to characterise device reverse and forward RDSon . In order to improve measurement sensitivity when device switches at high frequency, a trapezoidal current mode is proposed to measure device RDSon under almost constant current, which resolves measurement sensitivity issues caused by unavoidable measurement circuit parasitic inductance and measurement probes deskew in conventional device characterisation method by triangle current mode. Proposed measurement circuit and measurement method is then validated by first characterising a SiC-MOSFET with constant RDSon . Then, the comparison on GaN-HEMT dynamic RDSon measurement results demonstrates the improved accuracy of proposed trapezoidal current mode over conventional triangle current mode when device switches at 1MHz.

The energy consumption of an electric vehicle is due to the traction subsystem and also the comfort subsystem. If for a regular trip the traction energy can be relatively the same, the comfort energy has an important variation depending on the season temperatures. In order to plan the annual charging operation of an eco-campus, a simulation tool is developed for an accurate determination of the consumption of an electric vehicle all along the year. The developed model has been validated by comparison with experimental measurement with a real vehicle on a real driving cycle. Different commuting trips are analyzed for a complete year. For the considered city in France, the energy consumption leads to an overconsumption up to 33% in winter due to heating, and only 15% in Sumer due to air conditioning. Urban commuting driving cycle are more affected by the comfort than extra-urban trips.

In this study, we address the reduction of structural vibrations by means of an electromagnetic shunt damper (EMSD) combined with a mechanical dynamic vibration absorber (DVA). Two architectures, that differs in the placement of the EMSD with respect to the DVA, are tested, showing that one of them enhances the vibration control. In parallel, three shunt architecture are tested: a resistive shunt, a resonant conservative shunt and a resonant dissipative shunt. Optimal values of the EMSD and DVA parameters are obtained; then, the performances of all architecture, according to relevant criteria, are estimated and compared to a single DVA or a single EMSD. The case of a conservative DVA, that creates an anti-resonance, is particularly targeted. It is shown that the performances rely on two free parameters only: the mass ratio for the DVA and the electromagnetic coupling factor for the EMSD, thus giving generic abacuses that can be applied to any practical cases. Finally, experiments are proposed and a good agreement with the theoretical results is obtained, thus validating them.

This paper aims to investigate the approach combine the deep learning (DL) and finite element method for the magneto-thermal coupled problem.

This paper discusses the comparison of two series–parallel hybrid electrical vehicles. The first one is based on the Toyota hybrid system, while the second one is equipped with an electrical variable transmission. The problem with previous comparisons between these two transmissions is the lack of validated data used to support the comparison as well as a comprehensive study on the sizing of the electrical variable transmission for a given vehicle and load cycle. To tackle these issues, a validated model of an electrical variable transmission is used in combination with validated scaling laws to assess design changes. This scalable model is used to determine the optimal design and the impact of sizing on the fuel consumption of the vehicle. To exclude the impact of the chosen control methodology, dynamic programming has been used. This technique is not only used to optimize the operating points of the internal combustion engine, but also to find the optimal DC-bus voltage in order to optimize the system level efficiency. The comparison is performed for multiple driving cycles that all show the added value of the electrical variable transmission based hybrid electrical vehicle. On average, over the different driving cycles, a reduction in fuel consumption of 4.75% is achieved while using an electrical variable transmission.

In this article, an experimental procedure is presented to handle magnetic measurements under uniaxial tensile stress reaching the plastic domain. The main advantage of the proposed procedure is that it does not require an additional magnetic core to close the magnetic flux path through the studied sample. The flux flows only in the sample, and no parasitic air gaps are introduced, thus avoiding the use of the H-coil to evaluate the magnetic field, which is often very sensitive and not easy to calibrate. A specimen of nonoriented FeSi (1.3%) sheet (M330-35A) is characterized under uniaxial tensile stress. To validate the proposed procedure, a comparison with the single sheet tester procedure is carried out. The results obtained by the two procedures are in good agreement. Moreover, to illustrate the possibilities offered by the proposed procedure, we confirm some results obtained in the literature. We show that the positive plastic strain leads to a significant degradation of magnetic behavior. An applied tensile stress on a virgin (unstrained) sample leads to a degradation of the magnetic behavior. However, on a pre-strained sample, an applied tensile stress results in reducing the deterioration caused by the plastic strain until a stress value called optimum is attained. Above this threshold, the magnetic behavior re-deteriorates progressively.

The inclusion of higher-order terms in small-signal (modal) analysis augments the information provided by linear analysis and enables better dynamic characteristic studies on the power system. This can be done by applying Normal Form theory to simplify the higher order terms. However, it requires the preliminary expansion of the nonlinear system on the normal mode basis, which is impracticable with standard methods when considering large scale systems. In this paper, we present an efficient numerical method for accelerating those computations, by avoiding the usual Taylor expansion. Our computations are
based on prescribing the linear eigenvectors as unknown field in the initial nonlinear system, which leads to solving linear-only equations to obtain the coefficients of the nonlinear modal model. In this way, actual Taylor expansion and associated higher order Hessian matrices are avoided, making the computation of the nonlinear model up to third order and nonlinear modal analysis fast and achievable in a convenient computational time. The proposed method is demonstrated on a single-machine-infinite-bus (SMIB) system and applied to IEEE 3-Machine, IEEE 16- Machine and IEEE 50-Machine systems.

In this work, we investigate in Fe-Si laminations the core-loss coefficients variation with the flux density within the loss statistical approach framework. We find that the dynamical core-loss coefficients can be linked with the differential permeability defined from the low frequency normal curve. We interpret these variations as the fingerprint of the domain-wall activity (i.e. all the processes involving domain-wall movements, nucleation and anihilation) during the magnetization process. We show that the classical loss variation can be qualitatively described by the macroscopic formulation of the skin-depth, but not quantitatively.

During the operation of Claw Pole (CP) machines, and for some operating loads, the magnetic core temperature can reach 180°C in some hot spots. As a consequence, the core electromagnetic properties may considerably change, impacting the machine performances. In such a case, a deep knowledge of the electromagnetic behavior as a function of the temperature is required.

In this paper, we present a dedicated study of the CP rotor made from a forged magnetic steel. In fact, the CP magnetic properties heterogeneity and the claw shape made it necessary to extract specific samples that are characterized with a miniaturized Single Sheet Tester (SST). To that end, this work proposes a specific methodology to characterize the electromagnetic properties of the CP rotor material as a function of the temperature in order to better predict the machine electrical performances, especially regarding the iron losses.

Modular Multilevel Converter (MMC) is an established technology for HVDC or Multi-Terminal DC (MTDC) systems, due to its advantages over classical Voltage Source Converters (VSCs) such as two or three level VSCs. To achieve a full control of all state variables, it is essential to implement energy-based method in which a cascade control loop is employed to regulate all state variables including ac and differential currents, and stored energy within MMC arms. In addition to normal operation control, dc Fault Ride Through (DC-FRT) capability of the MMC is a crucial and challenging control issue especially for overhead line HVDC system where non-permanent dc fault occurrence is statistically more probable. Furthermore, the main problematic technical obstacle to develop HVDC/MTDC grids is the lack of mature dc fault protection. Since conventional control in normal operation cannot be employed in case of dc fault, an efficient control strategy is indispensable. The principal objectives of the novel control methodology are to (i) obtain DC-FRT capability, (ii) decay short circuit current to zero, (iii) secure the MMC through leg and arm energy balancing, (iv) support ac grid as a Static Synchronous Compensator (STATCOM) and (v) resume normal operation after dc fault clearance. The simulation results verify the validity of proposed control strategy to fulfill the abovementioned objectives in dc fault operation of the hybrid MMC.

Hysteresis models allow the prediction of iron losses in materials under complex magnetic excitation, with accuracy depending on their principle and identification procedure. Commonly, to achieve high accuracy, a model may require a broad set of experimental input data, which is in some cases, not easy to obtain. We propose, in this study, a static model focusing on simplicity while still striving for accuracy. Its principle is to represent the variation of the field deviation between reversal curves and a near saturation hysteresis loop. In terms of input data, this model requires the experimental first magnetization curve and a few quasi-static centered hysteresis loops of the material. Following the principle description, the identification procedure, the model validation, as well as a sensitivity study are presented in detail.

The manufacturing processes of electrical machines may lead to significant degradation of magnetic core
properties and therefore of the machine performance. Laminations are usually stacked and pressed which affects
the magnetic properties and the iron losses. However, the influence of this step must be still investigated when
large generators are considered. Indeed, in that case, the stator and rotor stacking process consists in assembling
several stacks of electrical steel sheets separated by airvents. The surface of the airvent spacers represents about
ten percent of the lamination surface of the magnetic circuit, implying, during the compaction process, an
inhomogeneous stress distribution with significant local stresses. The present work deals with the experimental
characterization of a lamination stack, including airvents, under compressive stress in the thickness direction. A
mock-up has been designed and built-up to study magnetic properties of lamination stacks under pressing
conditions corresponding to the industrial process.

In this paper, we propose a method to identify the magnetostrictive behavior of electrical steel sheet submitted to a mechanical loading. The technique relies on the use of a magneto-mechanical model including the magnetostrictive phenomenon, namely the anhysteretic Jiles-Atherton-Sablik (JAS) model, and experimental macroscopic
stress dependent magnetization curves. The method is illustrated with measured magnetization curves of a non-oriented (NO) electrical steel sheet under different stresses. Furthermore, the influence of a bi-axial mechanical
loading on the magnetostrictive behavior is analyzed with the help of an equivalent stress.

This paper presents the modelling of the DC-DC Multilevel Modular Converter (DC-DC MMC) with half-bridge Sub-Modules (SM) and the control based on the inversion of its model. The DC-DC MMC structure presents many advantages such as its modularity, the absence of capacitors on the high DC bus voltage and a very low switching frequency due to the large number of SMs. This topology also preserves the intrinsic disadvantages of the MMC as the complexity of modelling and controlling due to the large number of semiconductors and state variables to control. The control of this converter cannot be symmetrical due to the interconnection of the two parts by an internal AC grid. The control strategy of one part of the DC-DC MMC uses the conventional control scheme with currents controls and stored energy control. The second one uses the energy control and produces the waveform of the three-phase internal AC bus voltage linking the two parts of the converter. The explicit control for the generation of internal AC voltages guarantees the correct operation of the converter even in a critical DC voltage dip on one or the other DC buses. Thus, it avoids the need of a DC circuit breaker or the use of full bridge MMC sub-modules. The validity of the proposed control is verified by simulation using Matlab-Simulink.

Increasing nonlinearity in today’s grid challenges the conventional small-signal (modal) analysis (SSA) tools. For instance, the interactions among modes, which are not captured by SSA, may play significant roles in a stressed power system. Consequently, alternative nonlinear modal analysis tools, notably Normal Form (NF) and Modal Series (MS) methods are being explored. However, they are computation-intensive due to numerous polynomial coefficients required. This paper proposes a fast NF technique for power system modal interaction investigation, which uses characteristics of system modes to carefully select relevant terms to be considered in the analysis. The Coefficients related to these terms are selectively computed and the resulting approximate model is computationally reduced compared to the one in which all the coefficients are computed. This leads to a very rapid nonlinear modal analysis of the power systems. The reduced model is used to study interactions of modes in a two-area power system where the tested scenarios give same results as the full model, with about 70% reduction in computation time.

This paper investigates a real-time fault diagnostic of a transportation system which needs two drives with fault-tolerance capabilities. Because of constraints on the mass of the system and on the cost of the Voltage Source Inverter (VSI), a drive with two Six-Phase Permanent Magnet Synchronous Machines (PMSM) in series-connection supplied by two six-leg inverters is chosen. Despite the serial -connection, independent control of the two machines and fault –tolerance to open-switch fault is ensured. Nevertheless, a Fault Detection Identification (FDI) process is required for analysis and/or control reconfiguration. The proposed FDI is based on the combination of different criteria obtained from the two zero-sequence currents and from the normalized currents mapped into two frames defined by the Concordia Transformation. Results obtained from simulation and experimental tests show the effectiveness of the proposal.

Volatile productions and consumptions generate a stochastic behavior of distribution grids and make its supervision difficult to achieve. Usually, the Distributed Generators reactive powers are adjusted to perform decentralized voltage control. Industrial controllers are generally equipped with a local affine feedback law, which settings are tuned at early stage using local data. A centralized and more efficient tuning method should aim to maximize the probability that all the node voltages of distribution grids remain within prescribed bounds. When the characteristics of the stochastic power forecasts are known, the centralized algorithm allows to update the settings on a regular time basis. However, the method requires to solve stochastic optimization problem. Assuming that stochastic variables have Gaussian distributions, a procedure is given which guarantees the convergence of the stochastic optimization. Convex problems drastically reduce the difficulty and the computational time required to reach the global minimum, compared to nonconvex optimal power flow problems. The linear controllers with optimized parameters are compared to traditional control laws using simulations of a real distribution grid model. The results show that the algorithm is reliable and moreover fast enough. Hence, the proposed method can be used to update periodically the control parameters.

If multi-phase machines equipped with tooth concentrated winding with half a slot per pole and per phase offer interesting characteristics (simplified manufacturing, no space subharmonic, fault-tolerant ability), their low fundamental winding factors make their designs and controls challenging. The paper addresses the case of a seven-phase Surface-mounted Permanent Magnet (SPM) machine which has a fundamental winding factor lower than the third. This so-called bi-harmonic specificity is considered in order to achieve good torque quality (average value and ripples). Regarding the design, the magnet layer is segmented into two identical radially magnetized tiles that cover about three-quarters the pole arc. Regarding the control, the rated Maximum Torque Per Ampere (MTPA) supply strategy (h1h3 control) aims at generating a third harmonic current component greater than the fundamental. A prototype has been manufactured: the ability of the machine to provide smooth torque is experimentally confirmed through the implementation of a simple MTPA control which copes with high distortion in
no-load voltage.

In Active Distribution Networks (ADNs), Distribution Company (Disco) follows two main strategies of dispatching of Distributed Energy Resources (DERs) and trading energy with wholesale energy markets, including Day-Ahead (DA) and Real-Time (RT) markets, to meet the demand. An attempt is made in this paper to model the strategic behavior of the Disco, in the wholesale DA and RT energy markets, through a bi-level optimization approach While the objective of the upper-level problem is to minimize the expected cost of the Disco, the lower-level problem (with two optimization problems) formulates to simultaneously maximize the social-welfare of the DA market and minimize the cost of the RT market. Furthermore, uncertain behavior of renewable energy sources as well as demand is tackled into the problem formulation. To this end, Disco decision-making represents as a risk-based two-stage stochastic problem where the Disco’s risk aversion is modeled using conditional value at risk (CVaR) method. Generally stated, the proposed model is a non-linear bi-level problem which may be transformed into a non-linear but single-level problem through Karush–Kuhn–Tucker (KKT) conditions and dual theory. Detailed numerical results on a 6-bus and RTS 24-bus power systems are used to demonstrate efficiency of the proposed model. Moreover, sensitivity analysis is carried out to investigate the effect of risk-aversion parameter on the decision making of the Disco and the offers/bids in both the DA and RT markets.

The M2DC exploits the interleaving between the three legs of an MMC to realize a promising uninsulated DC/DC converter to interconnect HVDC grids. This paper details a current and energies decoupled model of the M2DC. The major idea proposed in this paper is focused on the full energy control generating optimal current references to minimize the internal currents magnitude. The energy sum and difference models are fully detailled. Both current and energy control loops are based on the model inversion principle in order to control all the state variables. The proposed control is based a dynamic control developed with the model inversion principle associated on an optimization of the current magnitude deduced from a quasi static analysis. All dynamics of the system are then explicitly controlled, which guarantee a good dynamic behavior during the transient. Therefore, current and energy controls are presented in details. Simulation results show the dynamic behavior of the converter for various operating points.

This paper describes a methodology for modelling a six-phase claw-pole alternator with its electrical environment. Magnetic
nonlinearities, eddy currents and rectifiers are taken into account. To solve magnetodynamic problems, we use the modified magnetic vector potential formulation. The complex structure of the machine requires a 3D finite element analysis. To limit the mesh size, we introduced a refinement strategy based on the calculation of the time derivative of magnetic vector potential, solution of the magnetostatic case. In addition, we propose to reduce the transient state by improving the initial solution from the solution of a magnetostatic problem. These different numerical techniques reduce drastically the computational time and memory resources. To validate the proposed approach, some results are compared with experimental ones.

In this article, the anhysteretic Sablik model is identified from measurements and implemented in a finite-element (FE) code.
The model takes into account the effect of the plastic deformation through the dislocation density, and thus, enables to account for the degradation of the magnetic properties. A new model for magnetostriction is proposed and implemented in the Sablik model. Experimental data are used to identify the parameters of both Sablik model and proposed magnetostriction. Furthermore, the mechanical punching process of an electrical steel sheet is simulated in view of evaluating the plastic strain distribution near the punched edge. Based on the Sablik model and the simulated plastic strain, FE simulations are carried out on a steel sheet and a cage induction machine. The effect of the punching process on the distribution of magnetic-flux density and the magnetization current is analyzed.

We investigate the effect of magneto-mechanical and magnetocrystalline anisotropies in a test application by coupling a multiscale magneto-mechanical model with a finite element method. This first application is composed of a cylindrical conductor surrounded by a ring composed of a non-oriented FeSi 3 % steel sheet which contains 396 representative grain orientations. Such an application can reveal the anisotropy due to the texture of the material by inducing a rotational flux density within the ring. Moreover, the effect of the texture and the magneto-mechanical characteristic of the steel sheets is analyzed in an axially laminated synchronous reluctance machine. The effect of stress strongly emphasizes the anisotropic behavior of NO steel sheets.

This article is interested in a controlled three‐phased voltage source inverter (VSI) for a grid‐connected wind power generator. The objective consists of participating in auxiliary services by enhancing the grid stability. An active wind generator associated with a battery/super‐capacitor storage system composes the studied renewable generator. It is related to a power consumer (load) to form a microgrid (MG) that can work according to grid stability in two modes: standalone and grid‐tied. Thus, the principal objective of this study is to develop a robust control method for MG connection with the grid to ensure the grid voltage and frequency regulation. This control has two control tasks: First, an adaptive droop control is implemented to adjust power flows exchanged with the grid to ensure its stability. It regulates its voltage and frequency. Second, a sliding mode control (SMC) with super‐twisting algorithm is put forward for the VSI to improve the regulation of the grid voltage and frequency under uncertainties. It improves control results concerning the reduction of harmonics caused by sudden variations of the load and of powers exchanged with the grid. It allows preventing the phenomenon of chattering created by classical sliding mode technique. Extensive simulation studies are carried out under MATLAB/Simulink. They prove the effectiveness of the suggested droop and SMCs compared with the classical proportional‐integral controller.

In this paper, residual type a posteriori error estimates developed in our previous work for magnetostatic and eddy current problems are extended to low-frequency (LF) Maxwell problems using A/φ formulation, where both inductive and capacitive effects can be handled simultaneously. Classical low order finite element basis (LOFEB), as well as high order finite element basis (HOFEB) of edge and nodal type are adopted in numerical examples to evaluate the performance of the proposed estimators.

In this work, the proper orthogonal decomposition (POD) is applied for parametric analysis in the gauged potential formulation of the Darwin model considering both capacitive and inductive effects. Due to the large contrast in material parameters, the resulted system matrix is ill-conditioned. Also, the condition number of the corresponding snapshot complex matrix is very huge. To improve the stability of the POD method, a structured-preserving strategy is considered and implemented for different unknown potentials, namely the magnetic vector potential A, the electric scalar potential φ, and the Lagrange multiplier p. Besides, a greedy algorithm is proposed to select the snapshots adaptively. Two numerical examples, including a parallel plate capacitor and a modified RLC device structure, are provided to illustrate the capability of proposed POD in model order reduction in frequency domain solvers.

The proper generalized decomposition (PGD) is ana priorimodel order reduction (MOR) method based on a variable-separatedexpression of the problem. Two iterative loops are needed in the PGD algorithm, namely the outer loop for enriching the reductionmodes progressively, and the inner loop for solving each mode by fixed point iterations. Setting the stopping criterion of these twoloops blindly can cause either the inaccuracy of the PGD or a waste of iterations. In this work, a special variable-separated PGDwith edge elements is proposed and implemented on a hexahedral mesh in magnetostatics. Also, an adaptive stopping criterion basedon dual formulations is applied to balance different error components, namely the discretization error, error for outer and innerloops of PGD. A numerical example is given to illustrate the proposed approach

For three-phase induction machines supplied by sinusoidal current, it is usual to model the n-bar squirrel-cage by an equivalent two-phase circuit. For a multiphase induction machine which can be supplied with different harmonics of current, the reduced-order model of the rotor must be more carefully chosen in order to predict the pulsations of torque. The proposed analysis allows to avoid a wrong design with non-sinusoidal magnetomotive forces. An analytical approach is proposed and confirmed by Finite-Element modelling at first for a three-phase induction machine and secondly for a five-phase induction machine.

The Maxwell Tensor (MT) method is widely used to compute global forces or local surface forces for vibroacoustic design of electrical machines under electromagnetic excitation. In particular, the air-gap MT method is based on a cylindrical shell in the middle of the air gap. This article proposes to quantify the differences between the air-gap MT and the magnetic force wave experienced by the stator. In particular, the air gap to stator transfer and the tooth mechanical modulation effects are studied. A new formula is proposed to extend the tooth modulation effect to tangential forces. A numerical application is performed with a turbo-alternator to illustrate the respective and combined effects of both phenomena. This article highlights that the tooth mechanical modulation is relevant even for electrical machines with a high number of teeth. In addition, the combination of the two phenomena has a clear impact on the calculated surface force. Therefore, it is recommended to take into account the air-gap transfer for any study of the tooth mechanical modulation effect.

This paper presents an optimization method that deal with control techniques for electrical machines, in order to impose a displacement with a minimum of energy consumption. It’s a generic method; However, its application to electrical machines is complex for implementation. The present work provides the shape of the optimal solution. Moreover, a resolution technique related to the nature of the model is proposed, which facilitate the numerical resolution of costate problem. The method is applied to hybrid stepper motor and the obtained results are then analyzed.

Grid-forming inverters usually use inner cascaded controllers in order to regulate the output AC voltage and the converter
output current. Yet, at the power transmission system level where the power inverter bandwidth is limited (i.e.; low switching
frequency), it is difficult to tune its controller parameters to achieve the desired performances because of the control loops
interactions. In this paper, a direct AC voltage control based state-feedback control is applied. Its control gains are tuned using
the linear quadratic regulator. In this paper, a sensitivity analysis is proposed in order to choose the right cost factors that allow
the system to achieve the imposed specifications. Conventionally, the system based on direct AC voltage control has no restriction on the inverter current. Hence, in this paper, threshold virtual impedance has been added to the state-feedback control in order to protect the inverter against overcurrent. The robustness of the proposed control is assessed for different short circuit ratio using small signal stability analysis, then, checked in different grid topologies using time domain simulations. An experimental test bench is developed in order to validate the proposed control.

Thermal performance of power converters is a key issue for the power integration. Temperatures inside active and passive devices can be determined using thermal models. Modelling the temperature distribution of high frequency magnetic components is quite complex due to diversity of their geometries and used materials. This paper presents a thermal modelling method based on lumped elements thermal network model, applied to planar magnetic components made of EE and E/PLT cores. The 3D model is automatically generated from the component’s geometry. The computation enables to obtain 3D temperature distribution inside windings and core of planar transformers or inductors, in steady state or in transient case. The paper details the proposed modelling method as well as the automated tool including the problem definition and the solving process. The obtained temperature distributions are compared with Finite Element simulation results and measurements on different planar transformers.

The present paper deals with the post-fault synchronization of a voltage source converter based on the droop control. In case of large disturbances on the grid, the current is limited via current limitation algorithms such as the virtual impedance. During the fault, the power converter internal frequency deviates resulting in a converter angle divergence. Thereby, the system may lose the synchronism after fault clearing and which may lead to instability. Hence, this paper proposes a theoretical approach to explain the dynamic behavior of the grid forming converter subject to a three phase bolted fault. A literal expression of the critical clearing time is defined. Due to the precise analysis of the phenomenon, a simple algorithm can be derived to enhance the transient stability. It is based on adaptive gain included in the droop control. These objectives have been achieved with no external information and without switching from one control to the other. To prove the effectiveness of the developed control, experimental test cases have been performed in different faulted conditions.

This paper studies the electromagnetic noise behaviour of a 5 phase Interior Permanent Magnet Machine with fractional slot concentrated winding designed. A numerical model is used for analysing the torque characteristics and electromagnetic forces. The vibro-acoustics and mechanical resonance of the model are then investigated analytically. The purpose of both analyses is to identify the source of electromagnetic noise within the machine. A sonogram is also carried out on the existing prototype to correlate it with the numerical results. Finally, the choice of the appropriate method to attenuate noise for this case study is elaborated.

Due to the intermittency and fluctuation of wind speed, the integration of wind power into electric power system has been a relevant issue. Recently, Pumped-storage hydro plant (PHES) can be used to balance the unstable output of wind farm, as it can adjust its production to compensate wind power fluctuation. This paper investigated the combination of a wind farm and a PHES facility from the point of view of a generation company in a market environment. A joint operation model between the wind farm and PHES is proposed. An algorithm of energy management system (EMS) is proposed to identify the daily operational strategy to be followed in order to:

1) Minimize the penalty cost resulted from wind-PHES output imbalances;

2) Maximize the daily revenue profit taking into consideration all constraints of joint operation.

Simulation results under MATLAB/SIMILINK®environment are presented and discussed.

The electromagnetic noise generated by the Maxwell radial pressure is a well-known consequence. In this paper, we present an analytical tool that allows air gap spatio-temporal pressures to be obtained from the radial flux density created by surface permanent magnet synchronous machines with concentrated winding (SPMSM). This tool based on winding function, a global air-gap permeance analytical model and total magnetomotive force product, determines the analytical air-gap spatio temporal and spectral radial pressure. We will see step-by-step their impacts in generating noise process. Also two predictive methods will be presented to determine the origin of the lows radial pressure orders noise sources. The interest lies in keeping results very quickly and appropriate in order to identify the low order electromagnetic noise origin. Then through an inverse approach using an iterative loop a new winding function is proposed in order to minimize radial force low order previously identified and chosen.

Control of Voltage Source Converters (VSC) based HVDC transmission systems is developed in this paper. The
proposed approach aims the stabilization of VSC, which is characterized by non-linearities due to requirements
of power flow and DC bus voltage. The steady state average model for the VSC-HVDC system is developed on linear
and bilinear deviation state space model around the working point. Based on poles placement and Least Squares (LS)
methods, linear and nonlinear polynomial feedback are considered. The proposed approach leads to regulate
simultaneously the dq grid currents and the DC bus voltage. By upon the time domain simulations in
MATLAB environment, effectiveness of the proposed control strategies are tested on a VSC and a
point-to-point VSC-HVDC transmission system. The simulation results show the robustness of the studied systems
under various conditions.

This paper addresses the volt-var control of distribution grids embedding many distributed generators (DGs). Specifically, it focuses on the compliance of powers to specified PQ diagrams at the high voltage/medium voltage (HV/MV) interface while the voltages remain well controlled. This is achieved using a two-stage optimization corresponding to two different classes of actuators. The tap position of capacitor banks is selected on a daily basis, given a stochastic model of the input powers prediction, which allows infrequent actuation and increases the device lifespan. In a second stage, a confidence level optimization problem allows to tune on an hourly basis the parameters of the DGs reactive power affine control laws. Results on a real-size grid show that the combined tuning of these actuators allows the ability to comply with European grid codes while the control effort remains reasonable.

Although the probability of occurrence of ac grounding faults at the valve-side of the interface transformer of a high-voltage direct-current (HVDC) link is low, they may cause high risks to the converter when compared to grid-side ac faults. This paper analyzes the characteristics of valve-side ac single-phase-to-ground faults in full-bridge modular multilevel converters (FB-MMCs) based bipolar HVDC systems. Overcurrents in the converter arms are analyzed and it is shown that overvoltages in FB submodules (SMs) occur without an appropriate protection in place. Two strategies are investigated to protect the FB-MMC during the fault and corresponding controllers are designed. The effectiveness of the presented strategies for the prevention of overcurrents and overvoltages, upon non-permanent and permanent faults, and system post-fault restoration are investigated. For completeness, the strategies are also verified by conducting simulations in PSCAD/EMTDC.

This paper presents a global optimization approach aiming to improve the energy efficiency of electrical machines. The process is made on a hybrid stepper motor allowing to simultaneously optimize design and command. This approach is
axed around Pontryagin's maximum principle, which is applied to a magnetodynamic model based on permeances network
model. The originality of the proposed approach is to obtain in the same process, the minimization of the energy by optimal
control and the minimization of the energy by optimal sizing.

The dq impedance stability analysis for a grid-connected current-control inverter is based
on the impedance ratio matrix. However, the coupled matrix brings the difficulties to derive its
eigenvalues for the analysis based on the General Nyquist Criterion. If the couplings are ignored for
simplification, the unacceptable errors will present in the analysis. In this paper, the influence of the
couplings on the dq impedance stability analysis is studied. For taking the couplings into account
simply, the determinant-based impedance stability analysis is used. The mechanism between the
determinant of the impedance-ratio matrix and the inverter stability is unveiled. Compared to the
eigenvalues-based analysis, only one determinant rather than two eigenvalue s-function is required
for the stability analysis. One Nyquist plot or polemap can be applied to the determinant for checking
the right-half-plane poles. The accuracy of the determinant-based stability analysis is also checked
by comparing with the state-space stability analysis method. For the stability analysis, the coupling
influence on the current control, phase-locked loop and the grid impedance are studied. The errors
can be 10% in the stability analysis if the couplings are ignored.

The modern control of power drives involves the consideration of electrical constraints in the regulator strategy,
including voltage/current limits imposed by the power converter and the electrical machine, or magnetic saturation due to
the iron core. This issue has been extensively analysed in conventional three-phase drives but rarely studied in multiphase
ones, despite the current interest of the multiphase technology in high-power density, wide speed range or fault-tolerant
applications. In this paper, a generalised controller using model-based predictive control techniques is introduced. The
proposal is based on two cascaded predictive stages. First, a continuous stage generates the optimal stator current reference
complying with the electrical limits of the drive to exploit its maximum performance characteristic. Then, a finite-control-set
predictive controller regulates the stator current and generates the switching state in the power converter. A five-phase
induction machine with concentrated windings is used as modern high-performance drive case example. This is a common
multiphase drive that can be considered as a system with two frequency-domain control subspaces, where fundamental and
third harmonic currents are orthogonal components involved in the torque production. Experimental results are provided to
analyse the proposed controller, where optimal reference currents are generated and steady/transient states are studied.

Modulated-Demodulated control (or vector control) allows to simultaneously impose amplitude and phase of a resonator. Moreover, the working frequency in the case of discrete-controller is substantially lower than the resonance frequency. However, the design of a such controller can be complex. In this paper, we outline a design directly in the baseband. To do so, the oscillator is modelled as a non-dimensional Multi-Input-Multi-Output system. An optimal control (Linear Quadratic Regulator) framework can then be used to design the controller. Thanks to ad hoc performances criteria, the weighting matrices are systematically specified according to the desired closed-lop time response. The methodology is validated by an experimental results on a plate actuated using piezoelectric patches.

Due to the variable nature of wind resources, the integration of wind power into electric power system has been a relevant issue. Recently, pumped hydro energy storage can be used to balance the unstable output of wind farm, as it can adjust its production to compensate wind power fluctuation. This article investigated the combination of a wind farm and a pumped hydro energy storage facility from the point of view of a generation company in a market environment. A joint operation model between the wind farm and pumped hydro energy storage is proposed. An algorithm of energy management system is proposed to identify the daily operational strategy to be followed in order to (1) minimize the penalty cost resulted from wind-pumped hydro energy storage output imbalances and (2) maximize the daily revenue profit taking into consideration all constraints of joint operation. Simulation results under MATLAB/Simulink® environment are presented and discussed.

Teleoperation of unmanned ground vehicles (UGVs), particularly for inspection of unstructured and unfamiliar environments still raises important challenges from the point of view of the operator interface. One of these challenges is caused by the fact that all information available to the operator is presented to the operator through a computer interface, providing only a partial view of the robot situation. The majority of existing interfaces provides information using visual, and, less frequently, sound channels. The lack of situation awareness (SA), caused by this partial view, may lead to an incorrect and inefficient response to the current UGV state, usually confusing and frustrating the human operator. For instance, the UGV may become stuck in debris while the operator struggles to move the robot, not understanding the cause of the UGV lack of motion.

When using magnetic vector potential (MVP)-based formulations for magnetostatic or eddy-current problems, either gauge conditions specifying the divergence of the MVP or tree gauging by eliminating redundant degrees of freedom of the MVP is usually imposed to ensure uniqueness of solutions. Explicit gauging of the MVP is not always necessary since classical iterative solvers can automatically and implicitly fix the gauge as long as the right-hand side vectors are consistent. Besides iterative solvers, implicit gauging is also observed when using state-of-the-art parallel sparse direct solvers (PSDSs), thanks to the built-in functions of handling null-spaces of either real symmetric positive semi-definite matrix systems or those complex symmetric systems from eddy-current problems. Both static and eddy-current examples are solved by PSDS to demonstrate results of local physical quantities or global quantities such as magnetic energy or joule losses. High-order edge/nodal elements are also considered in our numerical examples and it is observed that PSDS can also easily and correctly handle the delicate discrete null spaces.

Calculating the bounds of global energy is an important issue in computational electromagnetism, which can provide guaranteed results when extracting inductance parameters. In this paper, an improved equilibrated type a posteriori error estimate for open boundary magnetostatic problems is proposed. We derive our error estimator based on vector dual formulations, which can be efficiently solved using parallel sparse direct solvers. The new estimator can provide a sharp and guaranteed estimate of the finite-element spatial discretization error. Moreover, the computational cost is cheaper than using existing equilibrated error estimators. Numerical experiments are carried out to showcase the performance of our error estimator, including the modified TEAM workshop problem 13 and the benchmark IEEJ problem.

Dual formulations are accurate in use for computing energy-related global quantities such as inductance and providing upper and lower bounds of the unknown true values of these global parameters, which is not possible if using a single formulation. Since traditional dual formulations result in totally different algebraic matrix equations, people have to develop two different finite element programs and solve the resultant two algebraic equation systems respectively. In this work two practical dual formulations
for open region magnetostatic problems, where the global finite element matrices are exactly the same, are adopted for extracting the winding inductances. Finite element formulation and implementation details are presented. Practical examples having complex windings are solved using the proposed methods to showcase the effectiveness and accuracy. High order FE basis functions are also used to enhance the solution accuracy. The proposed method is highly useful for medium-sized industrial applications by providing guaranteed inductance parameters.

In this paper, a symmetric field-circuit coupled finite element method (FEM) for low-frequency (LF) full-wave Maxwell problems using a magnetic vector potential (MVP) formulation is proposed. The resultant fully-discrete coefficient matrix is made symmetric for the first time by introducing the so-called source electric scalar potential (ESP) for solid conductors, where the terminal currents are converted from surface integrations of the current density vectors to volumetric integrations. Numerical examples, including a benchmark capacitor charging problem with external circuit connections, are solved and the numerical results match well with reference solutions. The proposed formulation is useful when analyzing electromagnetic fields with coupled inductive-capacitive effects and external circuit connections.

An improved starting point Newton method applied to 3-D scalar formulation in magnetostatics is proposed in this paper. Compared with the classical Newton method, the inexact-Newton and quasi-Newton methods are reported by testing on a benchmark problem as well as an industrial example. Remarkable convergence acceleration using the proposed strategy is observed, and thus, it significantly
reduces the computational time.

In this paper, a novel potential formulation for low-frequency (LF) applications taking into account both inductive and capacitive effects but without considering wave propagation is proposed. Both time-domain and frequency-domain formulations are presented.
The resultant fully discrete finite-element matrix is made symmetric by incorporating a gauge condition and also rewriting the current continuity equation. To improve numerical accuracy and computational efficiency, high-order mixed-edge elements and nodal elements are adopted to approximate the vector and scalar unknown variables together with high-order time-stepping schemes. Several numerical examples are solved to validate and showcase the accuracy of the proposed methods. The proposed formulations are stable in use for LF electromagnetic field computations by considering inductive and capacitive effects simultaneously, such as finding the resonant frequencies of wireless power transfer devices.

An experimental approach is proposed to study the influence of the punching on the magnetic behavior of a stator core strips. Specimens of a non-oriented M330-A35 punched lamination sheet are picked up from a real manufacturing process. The proposed approach is based on the use of two types of specimens; one is a closed magnetic circuit while the second one is split into two parts. Magnetic measurements are performed on both types and compared with those made on specimens cut by WEDM which has a lower impact on the magnetic behavior. The specific purpose of this paper is to investigate the impact of punching in presence of an air gap that exists in electrical machines between rotor and stator. Therefore a dedicated device, optimized by FEM simulations, is developed in order to account accurately the air gap.

Claw pole machine performances are strongly related to the electromagnetic properties of ferromagnetic materials. These properties are impacted by the manufacturing processes, in a heterogeneous way, as well as by the thermal behavior of the machine and the mechanical stress distribution. Due to the complexity of CP geometry, extracted samples cannot respect the dimensions prescribed in international standards of electric and magnetic measurements. This paper proposes a specific methodology to characterize the electrical conductivity and the magnetic behavior of massive parallelepiped specimens extracted from different locations of a CP rotor.

In the field of tactile feedback, researchers try to generate localized stimulations on screens. Some solutions such as time reversal or phased array use vibration induced in the screen equipped with piezoelectric ceramics. We propose to use the modal basis to reproduce a specified velocity field on such devices. We explain the theory and propose a methodology to practically synthesize the voltages to achieved a controlled focusing in a given time. Experiments on a simple demonstrator are in good agreement with the theory for various velocity fields and a reduced number of modes.

This paper was focused on the implementation of experimental test bench for a wind power generator (WPG) connected to the electrical network. The objectives of this work are to validate the test bench functionality and to investigate in real time a high‐order sliding‐mode control (SMC) scheme applied to control the WPG. This study has three main purposes. The first one is the development of the SMC technique to ensure a control method insensitive against nonlinear behavior of wind systems. The second one is the experimental implementation of this SMC scheme. The third one is a synchronization technique that has been presented in a grid‐connected power inverter to adapt the WPG voltage to the grid voltage. A comparative study between the experimental and simulation results demonstrates the functionality of the test platform and the robustness of the SMC in real time.

The calculation of the probability of detection in non-destructive eddy-current testing requires the solution of a stochastic model requiring numerous calls of a numerical model leading to a huge computation time. To reduce this computation time, we propose in this paper to combine either the use of a stochastic metamodel or a mapping which avoids the remeshing step. The stochastic metamodel is constructed using the least-angle regression method. This approach is tested on an axisymmetric problem with six random input paramters which shows its efficiency and its accuracy.

In the context of future Permanent Magnet Synchronous Machines (PMSMs) with a high number of phases (>7) in integrated drives, this paper proposes several control strategies when multiphase PMSMs with non-sinusoidal back electromotive forces (back-EMFs) operate in healthy and open-circuit faults. In all operation modes, the considered constraint on current is related to the maximum root mean square (RMS) current allowable in one phase of the machine. The constraint on voltage limits the maximum peak value of the phase voltage determined by the DC-bus voltage of the converter. When one or two phases are open-circuited, to maximize torque and respect the constraints, new current references obtained by several proposed methods in rotating and natural frames are imposed to the machine. Due to the non-sinusoidal waveform of back-EMFs and the considered constraints, numerical computations based on analytical formulations are required to obtain maximal torque-speed characteristics, including the flux-weakening operation. The usefulness of the proposed strategies is verified by numerical and experimental results.

This paper proposes several easy-to-implement control strategies when seven-phase axial flux brushless DC machines with trapezoidal back electromotive forces operate in normal and faulty modes by taking into account constraints on voltage and current. The constraints are related to the converter and machine design in terms of maximum values of current and voltage. The considered faults are cases in which one or two phases of the machine are open-circuited. Numerical computations based on analytical formulations are applied to obtain torque-speed characteristics, including the flux-weakening operation. The methods determine current references to ensure the torque optimizations while currents and voltages are within their limits. The usefulness of the methods is verified by numerical results.

Multiphase machines have recently gained interest in the research community for their use in applications where high power density, wide speed range and fault-tolerant capabilities are required. The optimal control of such drives requires the consideration of voltage and current limits imposed by the power converter and the machine. While conventional three-phase drives have been extensively analyzed taking into account such limits, the same cannot be said in the multiphase drives’ case. This paper deals with this issue, where a novel two-stage Model Predictive optimal Control (2S-MPC) technique is presented, and a five-phase permanent magnet synchronous multiphase machine (PMSM) is used as a case example. The proposed method first applies a Continuous-Control-Set Model Predictive Control (CCS-MPC) stage to obtain the optimal real-time stator current reference for given DC-link voltage and stator current limits, exploiting the maximum performance characteristics of the multiphase drive. Then, a Finite-Control-Set Model Predictive Control (FCS-MPC) stage is utilized to generate the switching state in the power converter and force the stator current tracking. An experimental validation of the proposed controller is finally provided using a real-time simulation environment based on OPAL-RT technologies.

In order to better predict the high frequency switching operation of transistors in power converters, parasitic elements of these devices such as resistances, inductances and capacitances must be accurately evaluated. This paper reports on the characterization of a gallium nitride (GaN) packaged power transistor using S-parameters in order to extract the device parasitics. Because the transistor is packaged, a calibration technique is carried out using specific test fixtures designed on FR4 printed circuit board (PCB) in order to get the S-parameters in the transistor plane from the measurement. The proposed method is suitable for a wide range of power devices. In this work it is applied to an enhancement mode GaN High Electron Mobility Transistor (HEMT).The impact of junction temperature on drain and source resistances is also evaluated. According to characterization results, equation-based modeling is proposed for the non-linear parameters. The extracted parasitic elements are compared with reference values given by the device manufacturer.

The human perception of square ultrasonicmodulation of the finger-surface friction was investigated duringactive tactile exploration by using short frictional cues of varyingduration and sharpness. In a first experiment, we asked participantsto discriminate the transition time and duration of short squareultrasonic reductions of friction. They proved very sensitive todiscriminate millisecond differences in these two parameters withthe average psychophysical thresholds being 2.3–2.4 ms for bothparameters. A second experiment focused on the perception ofsquare friction reductions with variable transition times anddurations. We found that for durations of the stimulation largerthan 90 ms, participants often perceived three or four edges whenonly two stimulations were presented while they consistently felttwo edges for signals shorter than 50 ms. A subsequent analysisof the contact forces induced by these ultrasonic stimulationsduring slow and fast active exploration showed that two identicalconsecutive ultrasonic pulses can induce significantly differentfrictional dynamics especially during fast motion of the finger.These results confirm the human sensitivity to transient frictionalcues and suggest that the human perception of square reductions offriction can depend on their sharpness and duration as well as onthe speed of exploration.

In the context of traction drives with required torque transient capabilities and a classically wide flux weakening speed range, this paper gives design considerations of a particular Double-Polarity (DP) five-phase machine. Beyond its intrinsic fault tolerance due its five phases, it specificity is the ability to develop torques of comparable values under three kinds of supply: with only first, third or both first and third sinusoidal currents. This property, due to first (E1) and third (E3) harmonic electromotive forces (emf) of comparable values, gives more degrees of freedom for the control of the machine. Unlike three-phase sinusoidal machine, flux weakening is no more the unique solution when maximum voltage is reached. Thanks to the extra degrees of freedom in this kind of machines, more possibilities for the control of the torque and current supply can be applied. At first, elements for the choice of slots/poles combination of such DP machines are given. Then, in case of an Interior Permanent Magnet Synchronous Machine (IPMSM), possible adaptations of the rotor are proposed in order to bring the double p/3p polarity property. The last design criterion considered is the level of eddy-current losses, important at high frequencies. For proof of the concept effectiveness, a prototype with a five-phase fractional-slot concentrated winding of 40 slots and 16/48 poles is presented with results from experimental set-up and Finite Element modeling. A comparison with equivalent no-fault-tolerant three-phase 24 slots /16 poles machines is also carried out

In this paper a guaranteed equilibrated error estimator is developed for the 3D harmonic magnetodynamic problem of Maxwell’s system. This system is recasted in the classical A-phi potential formulation and solved by the Finite Element method. The error estimator is built starting from the A-phi numerical solution by a local flux reconstruction technique. Its equivalence with the error in the energy norm is established. A comparison of this estimator with an equilibrated error estimator already developed through a complementary problem points out the advantages and drawbacks of these two estimators. In particular, an analytical benchmark test illustrates the obtained theoretical results and a physical benchmark test shows the efficiency of these two estimators.

The high quality of electrical power in high power and high reliability applications is a crucial necessity even under fault mode function. However, in these conditions, the quality of the torque is a key feature. To overcome this problem, the multiphase permanent magnet (PM) motors seems to be a very attractive choice. In order to highlight the robustness and reliability of this technology, this paper investigates the control of a five-phase PM motor under an open circuited phase fault conditions. Moreover, a High Order Sliding Mode (HOSM) controller combined to an optimal reference current generation is tested and compared to a PID controller under fault mode conditions. This original control strategy is proposed for faulted conditions. Compared to classical fault tolerant control, this strategy allows a better dynamic tracking of the non-sinusoidal reference currents and leads to a smooth torque with minimal losses even in severe fault conditions. To validate the proposed control strategy, simulation, and experimental results are presented and discussed.

Distributed generators (DG) reactive powers are controlled to mitigate voltage overshoots in distribution grids with stochastic power production and consumption. Classical DGs controllers may embed piecewise affine laws with dead-band terms. Their settings are usually tuned using a decentralized method which uses local data and optimizes only the DG node behavior. It is shown that when short-term forecasts of stochastic powers are Gaussian and the grid model is assumed to be linear, nodes voltages can either be approximated by Gaussian or sums of truncated Gaussian variables. In the latter case, the voltages probability density functions (pdf) that are needed to compute the overvoltage risks or DG control effort are less straightforward than for normal distributions. These pdf are used into a centralized optimization problem which tunes all DGs control parameters. The objectives consist in maximizing the confidence levels for which voltages and powers remain in prescribed domains and minimizing voltage variances and DG efforts. Simulations on a real distribution grid model show that the truncated Gaussian representation is relevant and that control parameters can easily be updated even when extra DGs are added to the grid. The DG reactive power can be reduced down to 50 % or node voltages variances can be reduced down to 30 %.

The Modular Multilevel Converter (MMC) represents the important technological innovation that emerged among the diverse available topologies of VSC and is avowedly the most suitable solution for converters in HVDC (High Voltage Direct Current) transmission and MTDC (Multi-Terminal Direct Current) grids. Special focus is given through this paper to the dynamic performance of an MMC-based, back-to-back HVDC system. Using an optimal guaranteed cost control theory, a robust control approach is designed in order to reject the impact of the unmodeled uncertainty in the AC side of the MMC converter. For this aim, a small-signal state-space linear model is derived for the control design of an advanced local controller of each MMC station. Furthermore, a new optimal guaranteed cost controller is proposed based on convex optimization problem using LMI optimization theory. The proposed approach leads to regulate simultaneously the AC grid and differential currents as well as total stored energy per phase in abc frame. To ensure the energy balancing between upper and lower arm per phase, an outer control loop is used to control the energy difference per phase between upper and lower arms of MMC. For the MMC linked to HVDC system, the active power reference input is generated through an outer classical DC voltage controller. This combined control strategy between classic and advanced robust regulation methods allows exploiting the advantages of both control methods. Effectiveness of the proposed optimal robust control strategy for back-to-back MMC-HVDC system is evaluated across accurate and skillful simulation study under Matlab/SimPowerSystem environment.

The combination of batteries and supercapacitors is promising in electric vehicles context to minimize battery aging. Such a system needs an energy management strategy (EMS) that distributes energy in real-time for real driving cycles. Pontryagin’s minimum principle (PMP) is widely used in adaptive forms to develop real-time optimization-based EMSs thanks to its analytical approach. This methodology leads to an off-line optimal solution which requires an extra adaptive mechanism for real-time applications. In this paper, a simplification of the PMP method is proposed to avoid the adaptation mechanism in real-time. This new EMS is compared to well-known conventional strategies by simulation. Furthermore, experimental results are provided to assess the real-time operation of the proposed EMS. Simulation and experimental results prove the advantages of the proposed approach by a reduction up to 50% of the batteries rms current on a real-world driving cycle compared to a battery-only EV.