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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.

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.

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.

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.

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

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.

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.

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.

DOI: 10.1109/TVT.2020.3047219

DOI: 10.3390/en13215538

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.

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.

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.

Simulation is a valuable tool to evaluate energy consumptions and design of railway systems. The system limitations have an important influence on the system behavior and must be taken into account in the simulation. Especially, the electro-mechanical limitations have an impact on the kinematical behavior. However, such limitations are often neglected in classical studies. This paper deals with the development of an adaptive electro-kinematical simulation to adapt the kinematical behavior according to the system’s limitations. A flexible simulation tool is obtained by taking into account electrical, mechanical, and kinematical limitations. This tool is experimentally validated on a real railway track. It is then used to study solutions to increase the transport capacity of a subway system, even when limitations occur.

Multi-train systems are complex to study due to the size of the system and its specificities. To tackle these difficulties, this paper develops a reduced-scale power Hardware-In-the-Loop (HIL) simulation dedicated to subway lines emulations. Energetic Macroscopic Representation (EMR) is used to organize the HIL simulation. A first mono-train HIL simulation is developed and validated by experimental results. The HIL simulation is then extended to a two-train study to analyze the different power flows between subsystems.

For an accurate evaluation of the driving range of an Electric Vehicle (EV), many conditions must be considered (road profile, traffic influence, etc.). However cabin heating system is not often considered despite its significant impact. In this paper, the impact of the cabin heating system is studied on the driving range of an EV. A real EV is used as a reference. A multi-domain model is developed and validated by experimental results on the vehicle. From this validated model, the impact of the heating system on the range is evaluated up to 30% in cold climatic conditions. In a classical approach, an eco-driving mode enables an increase in the range by reducing the vehicle acceleration and velocity. When considering the heating system, the energy balance is more complex: the eco-driving mode can lead to an over-consumption of energy. A better compromise is required as a function of the climatic condition

This research work aims to study the impact of the heating system on the fuel consumption of a hybrid electric vehicle (HEV). The thermal engine is less used in an HEV than in a thermal vehicle, thus the cabin heating is partly ensured by electrical resistances. However, because the battery is partly charged by the thermal engine, this electrical heating has an impact on the fuel consumption. In the present work, a multi-domain model is proposed to analyze the impact of the heating system on the fuel consumption of a HEV. The models of the different physical subsystems are organized and unified by energetic macroscopic representation (EMR). Experimental validations, with an accuracy of 95%, are provided for each subsystem model. The validated simulation models are used to study the impact of the heating system for a specific driving cycle and climatic condition. For a simple energy management strategy (EMS), there is an over-consumption of 19% that is due to the heating system. When a more efficient EMS is used, the over-consumption is reduced to 12%. This study shows the interest in developing advanced energy management strategies that couple the traction and the heating functions of the vehicle.

Simulation is a valuable way to develop cleaner transportation systems. Nevertheless, the complexity of this kind of system conducts to complex models, especially to take into account non-linear aspects of traction power substations (TPS). This paper proposes thus different TPS models based on the Energetic Macroscopic Representation. An appropriate model is deduced from comparisons between the different models to realize energetic studies. It is finally applied to the simulation of a simple subway line, which is experimentally validated.

In the simulation of new vehicles, the Internal Combustion Engine (ICE) is generally modeled by a static map. This model yields the mechanical power and the fuel consumption. But some studies require the heat energy from the ICE to be considered (i.e. waste heat recovery, thermal regulation of the cabin). A dynamical multi-physical model of a diesel engine is developed to consider its heat energy. This model is organized using Energetic Macroscopic Representation (EMR) in order to be interconnected to other various models of vehicle subsystems. An experimental validation is provided. Moreover a multi-physical quasi-static model is also derived. According to different modeling aims, a comparison of the dynamical and the quasi-static model is discussed in the case of the simulation of a thermal vehicle. These multi-physical models with different simulation time consumption provide good basis for studying the effects of the thermal energy on the vehicle behaviors, including the possibilities of waste heat recovery.

This paper deals with the analysis and simulation of an electric vehicle, coupling functional and structural approaches in the same simulation environment. The Bond Graph model, the structural approach, is first deduced from the physical system, which in turn produces a direct correspondence between the system and its model. The control structure is then easily deduced from the Energetic Macroscopic Representa- tion, the functional approach, of the vehicle using a systematic procedure. Simulation results are provided in order to analyze the performance of the closed-loop system

This paper studies the influence of an Energy Storage System (ESS) on the fuel consumption of a diesel-electric locomotive. First, an energetic model of a diesel-electric locomotive is established using Energetic Macroscopic Representation. An inversion-based control is deduced, and the model is validated by experimental results on a real locomotive. Secondly, from this validated model, a battery/supercapacitor ESS is added in simulation in order to study the benefit of the hybridization before integration on the real vehicle. The simulations show that a simple energy management based on a frequency approach allows the reduction of 25% the fuel consumption on a real drive cycle.

This paper aims to compare different models and simulation approaches for an energetic simulation of an automatic subway. For this purpose, several models are carried out from a dynamic model which is validated by comparison with experimental measurements. Furthermore, two different simulation approaches are compared: backward and forward approaches. A simplified model is obtained and allows the reduction of the simulation time by 96 compared to the dynamic model by keeping an accuracy of more than 99 %.

(common paper of L2EP Lille, and PSA Peugeot Citroën within MEGEVH, French network on HEVs, extended version of the Award Paper Prize of IEEE-VPPC 2012) The new engineering challenges lead to a control of a vehicle more and more complex. To tackle this issue, Hardware-In-the-Loop (HIL) simulation is used in the development of real-time embedded systems. In this paper, the control of a double parallel hybrid vehicle is validated using a reduced power HIL simulation. A graphical description is used in order to organize the emulation and control. Some experimental results of a versatile testbed are given for the Peugeot 3∞8 HYbrid4.

Automotive engineers and researchers have proposed different topologies for series–parallel hybrid electric vehicles (SP-HEVs). The Toyota Hybrid System (THS) is the best known SP-HEV-based vehicle, but alternative solutions, such as electric variable transmission (EVT), have been also proposed. An efficient comparison between these different solutions is a key point to estimate the added value of each topology. This paper presents the application of optimal control to two series–parallel hybrid architectures for efficiency assessment purposes. The dynamic programming method is applied to the THS and to a virtual hybrid vehicle with an EVT. The way to take into account the supplementary degree of freedom provided by the decoupling of the wheels and the engine in both topologies is presented. The optimal fuel consumption is then compared on different driving cycles and brings out an overconsumption of the EVT topology. Then, a parametric study shows that inserting an appropriate gear ratio on the internal-combustion-engine (ICE) shaft can improve the EVT efficiency that becomes close to the THS efficiency.

This paper deals with the control design of a military hybrid electric vehicle (HEV). The studied vehicle presents a highly redundant architecture to ensure high system reliability. As a consequence, the control scheme is complex to design. Energetic macroscopic representation (EMR) is used to describe the interaction between all subsystems of the powertrain. A control structure is deduced by an inversion of the EMR of the vehicle powertrain. Simulation results demonstrate the ability of this inversion-based control to achieve military missions.

This paper presents a Proton Exchange Membrane Fuel Cell model suitable for water management analysis. In order to be integrated into a complete fuel cell vehicle simulation for real-time control and energy management designs, Energetic Macroscopic Representation is used. An experimental validation is performed and electric and gaseous behaviors are studied in particular. The integration of the developed model into a vehicle simulation, in which the FC is used as a range extender, demonstrates the use of the model and allows the study of the behavior of this system.

In this paper, a new Energy Storage System (ESS) is developed for an innovative subway without supply rail between two stations. The ESS is composed of a supercapacitor bank and a braking resistor. An inversion-based control of the ESS is deduced from the Energetic Macroscopic Representation of the entire system. This control scheme requires a distribution crite-rion in order to allow the energy to be shared between the supercapacitors and the braking resistor. Different cases are evaluated via a Hardware-In-the-Loop simulation using a re-duced power ESS. The suggested control enables the energy recovery to be maximal and secure the supercapacitor in real time for different track configurations.

An innovative subway without supply rail is presented. This article deals with the sizing of the required onboard energy between two stations in the worst case. The influence of the system limitations on this sizing is studied. It shows the importance of the system limitations to design the energy storage subsystem.

An innovative subway has been proposed using supercapacitors as the main energy source. Different steps have been defined in order to check the performance of this new supply system on a real subway. In this paper, a reduced-scale Hardware-In-the-Loop simulation is presented for initial experimental vali-dations on a reduced power experimental set-up. Special attention is paid to reproducing torque, acceleration and jerk limitations of the real system.

This paper presents a model of a whole polymer electrolyte fuel cell system including the stack, an air compressor, a cooling system and a power converter. This model allows its integration in a complete hybrid electric vehicle simulation. The level of detail of the model is chosen to enable control rules design, ancillaries sizing and study of the interaction between the components of the vehicle. This model is formalized with Energetic Macroscopic Representation (EMR), thus organized in a unified multi-domain graphical description. Experimental results are compared to simulations for validation of the model accuracy.

An innovative subway has been proposed using supercapacitors as energy source. In this paper are presented, different possibilities to reduce on-board stored energy in order to downsize the on-board energy storage subsystem. Special attention is paid to the influence of a feeding rail extension or a downward slope at the beginning of the interstation on the on-board stored energy. A map is built to facilitate the selection of the solution which leads to reduce the on-board energy.

A storage supercapacitor subsystem is studied for insertion in a series hybrid electric vehicle. This subsystem is composed of a supercapacitor bank and a braking resistor used when the supercapacitor voltage is at its maximum value. Generally, when the maximum voltage is reached by supercapacitor, a voltage drop occurs because of the current cancellation in the series resistance of the supercapacitor. Thus the stored energy is reduced compared to the maximum value that could be reached. To overcome this drawback, new control strategies are proposed by acting on the braking resistor. Energetic Macroscopic Representation (EMR) is used to organize the numerous blocks required for modelling and control. Experiment results are provided and highlight the increase of energy storage.

Dual-drive gantry systems are commonly used in many industrial applications. However,as few papers are available in the literature, this kind of system is difficult to broach. Based on an energetic approach so-called Energetic Macroscopic Representation (EMR), this paper presents a graphical modelling based on lumped-parameters. The initial drive is decomposed into a set of decoupled fictitious systems using a mathematical transformation. Since the modelling respects the integral causality, inversion-based controls are thus deduced. More generally, this approach proposes a way to analyze and deduce models and controls of multi-drive mechatronic systems.

Abstract — Certain difficulties arise when attempting to model a clutch in a powertrain transmission due to its non-linear behav-iour. Two different states have to be taken into account: the first being when the clutch is locked and the second being when the clutch is slipping. In this paper, a clutch model is developed using Energetic Macroscopic Representation (EMR), which is in turn used in the modelling of complete Hybrid Electric Vehicles (HEVs). Two different models are used and a specific condition defining the commutation between both models with respect to the physical energy flow is proposed. A Petri net is employed to activate one of the models depending on the clutch state (locked or slipping). This model allows us to implement without difficulty a simulation of the clutch with a relatively short computation time.

AC machines supplied in parallel by a common voltage source inverter are sometimes used in industrial drives and railway traction applications. This reduction of power and control electronics leads to a reduction of cost, weight and dimensions that is very useful for on-board systems. But this common supply imposes common voltages to all machines and the possibilities of independent behavior are reduced. In this paper a graphical modeling is suggested to model such parallel drives for a railway application. A weighted control is then systematically deduced from this modeling and different possibilities of control are highlighted. Experimental results are provided to compare two of the deduced controls.

The control of a wind energy conversion system can be decomposed in two parts: a local control depending on the power structure and a global control (strategy) deduced from global considerations. The local part ensures an efficient energy management of each component of the system. The local control structure can be deduced from the Energetic Macroscopic Representation, which is a graphical description of the system according to action and reaction principle. Using inversion rules, the deduced control structure is composed of a maximum of control operations and measurements. The global control part is independent of the power structure. This strategy part leads to achieve power objectives (active and reactive power targets) and system constraints (machine efficiency and DC bus limitation). Several strategies can be defined for the same system. These control decomposition is applied to a wind generation system composed of a permanent magnet synchronous generator and two three-phase converters. Simulation results are provided for a 600 kW wind energy conversion system.

A fault tolerant AC-AC converter capable of supplying a three-phase induction machine from the grid with an unitary power factor has been proposed. With one faulted converter leg, two of the remaining five legs are connected to the grid, two legs are connected to the machine and a common leg is shared by the grid and the machine. The previously developed control strategy required a too great computation time for practical implementation. In this paper, a new control strategy is suggested for this power converter. It enables an easier control implementation. Experimental results are provided.

Behaviour model control (BMC) is known to increase the robustness of a process control. It has already been applied to electrical drives for single-loop controls. This paper introduces the BMC among others model control strategies and extends its single-loop structure to more complex controls, which need several loops. This extension is applied to a double loop control of a DC machine drive. Simulations and experimental results show that the suggested double-loop BMC yields better results than a classical control, increasing robustness against parameter variations and external disturbances.

A multi-machine multi-converter system formalism has been proposed to describe systems composed of several electrical machines and converters. This description points out coupling elements, which have to distribute energy. Control structures have already been proposed for systems with downstream coupling. This paper is focused on control structures for systems with upstream coupling. Several solutions can be found by moving control blocks

The control of a wind energy conversion system can be decomposed in two parts: a local control depending on the power structure and a global control (strategy) deduced from global considerations. The local part ensures an efficient energy management of each component of the system. The local control structure can be deduced from the Energetic Macroscopic Representation, which is a graphical description of the system according to action and reaction principle. Using inversion rules, the deduced control structure is composed of a maximum of control operations and measurements. The global control part is independent of the power structure. This strategy part leads to achieve power objectives (active and reactive power targets) and system constraints (machine efficiency and DC bus limitation). Several strategies can be defined for the same system. These control decomposition is applied to a wind generation system composed of a permanent magnet synchronous generator and two three-phase converters. Simulation results are provided for a 600 kW wind energy conversion system.

A vectorial formalism for analysis and design of polyphase synchronous machines without reluctance and saturation effects is described. We prove the equivalence of such a machine with a set of magnetically independent machines, which are electrically and mechanically coupled. Specific problems of polyphase machines can thus be favorably analyzed with this concept. Rules of conception and constraints on electric supply can be deduced. Moreover the vectorial approach, which generalizes the complex phasor method, can also be used to control n-leg Voltage Source Inverters. This methodology is applied to 3-phase and 6- phase synchronous machines.

A generic and simple control method is suggested for any multi-leg voltage-source-converter. A specific coding yields an inversion table allowing a fast practical implementation. Phase-to-phase voltage references have to be defined for such a table. This original control strategy is validated by experimental results for 2-leg, 3-leg, 4-leg and 5-leg structures supplying balanced and unbalanced multi-phase loads.

Le transport routier est aujourd’hui au cœur d’enjeux sociétaux majeurs. Les réserves limitées d’hydrocarbures et la pollution croissante impliquent la recherche d’une alternative crédible au véhicule à moteur à combustion interne. Dans cette optique, l’utilisation des piles à combustible semble prometteuse. Néanmoins, les performances, intrinsèquement bonnes, d’un tel groupe électrogène sont grevées par une consommation énergétique importante des auxiliaires nécessaires à son propre fonctionnement. Une étape déterminante réside donc dans la mise au point de modèles de simulation de ce groupe électrogène multiphysique par excellence et multiéchelle. Ces modèles permettront alors d’augmenter le rendement énergétique de ce groupe électrogène, au travers de lois de commande locales et globales optimisées. Cet article propose une modélisation basée sur la représentation énergétique macroscopique, ce formalisme visant à définir une représentation synthétique pour les systèmes complexes, respectant la dualité description structurelle/fonctionnelle, dans le cadre de la systémique (interactions) structuraliste (causalité intégrale). Un modèle de simulation en est déduit.

Un formalisme a été mis en place pour l’analyse de systèmes composés de plusieurs machines électriques et/ou plusieurs convertisseurs statiques. Il permet de mettre en évidence les trois couplages possibles dans les chaînes de conversion électromécanique : couplage électrique, magnétique ou mécanique. Des règles basées sur le principe d’inversion permettent de proposer des structures de commande pour de tels systèmes. Des critères de répartition énergétique doivent ainsi être mis en œuvre. Plusieurs exemples d’application très divers montrent l’intérêt de ce formalisme.

This paper aims to study the recharge time for a battery as a function of the temperature. An electro-thermal model is used for the battery to simulate the evolution of the battery internal temperature. The electrical parameters of the battery are dependent on the temperature and the state of charge. They have been characterized from an electric vehicle Lithium Iron Phosphate (LFP) cell. Instead of a classical Constant Current, Constant Voltage (CC-CV) technique, a current trajectory is used for charging. The goal is to recharge at maximal admissible current to be as fast as possible. The maximal admissible charge current is a function of the battery internal temperature. Simulation are performed for a 0 °C to 40 °C temperature range. The simulation results show that the fast charging is slower when the ambient temperature is increasing.

The Energetic Macroscopic Representation formalism is more and more used for the modelling and control organization of energy conversion systems. Many applications for electric vehicles have been developed using this formalism. If different simulation packages have included EMR libraries, there is still no drawing software dedicated to this formalism. To address this limitation, an open-source EMR drawing software is proposed in this paper. Our proposed software aims to provide a comprehensive solution for visualizing and organizing EMR models. By offering a user-friendly interface and compatibility with different word processing software, this tool contributes to the advancement and wider adoption of EMR in energy conversion system design and control.

he aim of this paper is to validate the compliance between an EV and a battery with a reference driving cycle. The Hardware in the Loop methodology is used. It is based on the interactions between the different EV subsystems. In this paper, a 35 kWh battery pack is studied. A 5 kWh module from this pack is tested with the same power constraints when used in the real EV. The developed power Hardware-in-the-Loop (HiL) test bench is composed of a model of the traction chain and a controllable current source. A driving velocity cycle is used as an input. The HiL test is achieved at full power scale for a module. It is shown that the tested battery could be used in the studied EV as the limits of the battery operation are not crossed for a WLTC velocity cycle.

This paper shows that the way of charging electric vehicle influences the battery aging. A simplified lithium-ion battery calendar aging model is used. This simple battery lifetime model, estimates the capacity fade including the effects due to the temperature and the state of charge. The reference vehicle is a 2018 Nissan Leaf. The entire vehicle, including the battery, the traction system and the road, is simulated with a reference velocity cycle. The energetic macroscopic representation of the vehicle is used for model and control organization. Two charging scenarios are defined. The first scenario corresponds to a daily vehicle charge, while the second one corresponds to one charge every 5 days. The model including the aging of the battery shows a significant difference between the two scenarios in term of capacity degradation through years.

The Toyota Mirai is a fuel cell vehicle with a hybrid energy storage subsystem (battery and fuel cell). Its small-size battery has a limited state-of charge (SoC) variation of only 10%. In order to reduce the fuel cell current peak, a new control scheme is proposed by merging two control laws. This merging offers a supplementary degree of freedom for the energy management strategy. In simulation, an increase the battery SoC variation by only 10% leads to 20% reduction of the fuel cell current for a WLTC driving cycle.

This paper studies the effect of the granularity of a cell model on the voltage accuracy. A multi-coupled cell model with varying parameters is compared with a simpler one (varying voltage source and equivalent series resistance). The first model implies a very long and complex characterization process. The second one is very simple. Experiments are performed at different temperatures by applying a current profile corresponding to a driving cycle of an electric vehicle. Experimental results show both models can be used for 25°C and 10 °C ambient temperatures with reasonable accuracy. Nevertheless, when the temperature is cold the multi-coupled model is more accurate.

The automotive industry is shifting to mass production of electrified vehicles. Simulation is a key step for developing these new vehicles. System simulation tools as Simcenter Amesim includes ready-to-use multi-physics libraries in that perspective. A new library is being created based on the Energetic Macroscopic Representation formalism to speed-up the battery electric vehicles (BEV) development process. The paper presents the BEV multi-level simulation where the simulations were done using 3 different levels for the battery models. By using “plug & play” method different BEV model configurations can be built in a fast, precise and systematic way.

Equivalent circuit models are widely used to describe the electrical behavior of batteries. They are also prioritized for energetic studies and driving range estimations of electric vehicles. This is mainly due to their simplicity and acceptable accuracy. This paper presents a comparison of the accuracy of two equivalent circuit models (Rint and Thevenin) under a driving scenario. For this, a Hardware-in-the-Loop simulation of a traction subsystem is used to impose a current profile into a real Li-ion battery module. This current profile is deduced from a reference velocity profile. Then, the measured battery voltage and current are compared to those of the simulated models, by imposing the same reference velocity. Results show a small error difference between the two models.

The driving range of electric vehicles is greatly reduced during winter. One of the reasons is the need for thermal comfort in the cabin. This paper presents a simulation program to assess the impact of cabin heating on the driving range. For this, a quasi-static model of the traction system, and a thermal model of the cabin, based on lumped parameters, are developed. Models are then organized and interconnected to build the simulation. Finally, the program is used to estimate the driving range on a winter scenario.

In conventional electric railway transportation systems supplied in DC, regenerative braking energy cannot be generally sent back to the electric power grid due to the non-reversible diode rectifiers used in traction power substations. However, a DC substation could be made reversible by connecting an inverter in parallel with the existing rectifier, hence allowing the energy recovery. This paper presents the development of a simulation program to quantify the braking energy that could be recovered with the addition of this power electronics device.

Hardware-in-the-Loop (HiL) simulation is more and more used during the development of hybrid electric vehicles (HEV). Power emulators are used to test different components of HEVs. However, there are several requirements that must be met for test accuracy and reliability. In this paper, time and frequency domain analyzes are combined to determine the ppropriate characteristics of a power emulator for testing the electrical generator of a series HEV.

This study deals with the driving range evolution of an EV as a function of the cumulated hours of operations. The studied vehicle is a three-wheel electric vehicle (e-TESC 3W platform) developed and instrumented at the University of Sherbrooke. The system model is built and organized using the Energetic Macroscopic Representation. A current cycle is applied with a programmable source on one cell to emulate the driving current constraints. The cell model parameters are characterized periodically. Then, the EV simulation is performed with the battery parameters corresponding to different cumulated driving hours. It is shown that the driving ranges is reduced by about 12% after 200 h of operations.

Parallel hybrid electric vehicles (HEVs) are suitable for heavy-duty applications like trucks. Yet there is an issue of this power configuration that the electrical drives have to work with many fluctuations which can degrade the batteries. Supercapacitors (SCs) can be added to save the batteries life-time. However, it also adds more losses to the system which can increase the engine fuel consumption. This paper aims to study the impact of SCs subsystem on fuel consumption and batteries life-time of a hybrid truck. Energetic Macroscopic Representation (EMR) is used to deal with the complexity of the studied system. A fair comparison is achieved by using dynamic programming due to its global optimal solutions. Simulation results figure out that the SCs subsystem causes 14% decrease of the maximum optimal saved fuel but can reduce up to 49% of batteries rms current for a specific hybrid truck. A positive effect of using hybrid energy storage subsystems for HEVs can be therefore concluded.

Optimization methods for Energy Management Strategy (EMS) are more and more used to minimize the fuel consumption of Hybrid Electric Vehicles (HEV). For off-line techniques, such as dynamic programming, from a given driving cycle, an algorithm is defined to determine the optimal power flows of the vehicle. Most of the time, the optimization is achieved by not considering the resistive force due to the road slope, which can be very high in certain roads depending on the mass of the vehicle. This paper aims to quantify the accurate fuel consumption economy when the road slope is integrated or not in the EMS optimization problem of a parallel HEV using dynamic programming.

Driving cycles can be generated by using instrumented vehicle or by simulation using a driving cycle generator. The advantage of the measurement on a real vehicle is to have real velocity profiles. But this method requires an instrumented vehicle and the time to carry on the tests when the weather conditions are acceptable. A driving cycle generator is proposed to avoid these problems. Comparison between the two methods is presented

Hybrid electric vehicles (HEVs) can be supplied by hybrid energy storage systems (H-ESSs). Such kind of system needs to be handled by complex energy management strategies (EMSs) considering several objectives. Besides, to evaluate such EMSs, an optimal benchmark could be developed. Dynamic programming (DP) is suitable for that purpose because of its ability to obtain the optimal solution. However, it is non-trivial to address a multi-objective energy management problem by using DP because of the complexity of the system and computational issues. This paper develops a DP-based optimal EMS for a hybrid truck supplied by battery/supercapacitor H-ESS using a bi-level optimization approach. This approach decomposes the EMS into optimal sub-strategies regarding the structure of the studied system. The validation of the optimal strategy is demonstrated by simulation results.

Simulation is a key step during the development phase of Hybrid Electric Vehicles (HEV). However, for a given objective of the simulation, several assumptions are made to determine the appropriate model of a HEV. Neglecting the rotating components mass, in comparison with the static mass of a vehicle, is a classical assumption made. In this paper, the influence of the rotating components mass on the fuel consumption of a plug-in parallel HEV is studied. Three models, related to the mass of the vehicle, are considered. In that aims, Energetic Macroscopic Representation is used to organize the different models of the powertrain. The effects on the fuel consumption are then studied. In fact, the fuel consumption of the studied vehicle is 7% lower when the rotating components mass is neglected.

Battery operation is influenced by the temperature. Thus, thermal modelling is an important aspect for battery electric vehicles (EVs). Generally the electro-thermal parameters are identified for one single cell. In EVs the battery is divided into several modules (groups of cells side by side). The objective of this paper is to quantify the accuracy by using the electro-thermal parameters of one single cell to model the behavior of a module. The temperature of a cell inside a module and the voltage of this module are recorded during a real driving cycle in an instrumented commercial EV. Considering the module as a group of identical single cells leads to an error of 7% for module voltage and 4.8% on the self-heating.

Hybrid energy storage systems (H-ESSs), as hybridizations of batteries and supercapacitors (SCs), need to be handled by appropriate energy management systems (EMSs). Smoothness of battery current to reduce their degradation are normally the aim of the EMSs. The evolutions of SC voltage however also need to be addressed. Various approaches for handling SC voltage while managing battery current can be found in the literature. Most of the time, their limitations are achieved directly or indirectly in the EMS. This paper aims to develop a merging control scheme to include the SC control outside the EMS. This control scheme based on the inversion principle of the Energetic Macroscopic Representation is proposed for a battery/SC subsystem. Two control schemes are thus systematically deduced and then merged. The battery current reference is generated regarding their aging behavior. Meanwhile, the SC voltage reference is deduced concerning the required SCs stored energy as a function of the vehicle velocity. The proposed approach is validated by simulation in Matlab/Simulink®.

Charging a battery packs is a critical point for electric vehicles (EVs). The customer is seeking for fast charging. However, the current level has a negative impact on the battery pack lifetime. This paper aims to study through simulation results the self-heating of a battery pack used in an EV as a function of the charging current. Energetic Macroscopic Representation (EMR) is used to organize the control of current and voltage of battery pack while coupling electrical and thermal domains. The study shows that the self-heating of an EV pack can be sizeable even under the EV manufacturer charging current limits. This is why EV manufacturers are advising customers to reduce the occurrence of fast charges.

Fuel consumption is a critical issue of hybrid vehicles, especially the heavy-duty ones. Studies on energy saving ability considering different power and energy capabilities of the electrical components are therefore of interest. This paper aims to compare the maximal fuel saving of the hybrid truck with different hybridizations. Modeling, control, and energy management of the system are carried out using Energetic Macroscopic Representation formalism. Dynamic programming is employed as a global optimization-based strategy for energy management of the vehicle. An 8.5-ton parallel hybrid truck primarily driven by a 147-kW internal combustion engine is under study. Simulation results point out a preferred hybridization option by using a 120-kW electrical machine supplied by a 19.4-kWh Li-ion battery pack. A respective 21.6% reduction of fuel consumption is reported for USA FTP Highway driving cycle.

To ensure the highest energy efficiency of Hybrid Electric Vehicles, optimizing their Energy Management Strategy (EMS) is required. Unfortunately, most of the methods for optimal EMS like Dynamic Programming (DP) cannot be used in real time. Rule-based EMS are well known to be easily usable in real time. The objective of this paper is to achieve a rule-based EMS of a parallel Hybrid Electric Vehicle, deduced from DP. In that aims, Energetic Macroscopic Representation of the powertrain is used to develop a backward model.

Energy management strategies are mandatory for hybrid energy storage systems in applications for electric and hybrid vehicles. Optimization–based real–time strategies are of interest since they are straightforward to optimize performance criteria. The available methods are often the combinations of adaptive mechanisms with solutions deduced by optimal control techniques such as Pontryagin’s minimum principle (PMP). This paper proposes an approach to develop a real–time strategy for battery/supercapacitor systems based on PMP and Energetic Macroscopic Representation without any need of adaptive mechanism for the co-state variable. Performances of the proposed strategy are validated by simulation.

The paper deals with the design and the control of a battery/supercapacitors energy storage system for a CVT-based hybrid electric truck. The battery/supercapacitors system is used as a secondary source in the vehicle instead of using a battery like conventional hybrid vehicles. The proposed vehicle represents then a complex system to control. Simulation results on a real driving cycle validate the energy management of the hybrid truck. The supercapacitors bank enables to avoid some battery current peaks, what is interesting for the battery lifetime. The battery size is furthermore reduced in comparison to a battery-only hybrid truck.

Energy management strategies are mandatory for hybrid energy storage systems in applications for electric and hybrid vehicles. Optimization-based real-time strategies are of interest since they are straightforward to optimize performance criteria. The available methods are often the combinations of adaptive mechanisms with solutions deduced by optimal control techniques such as Pontryagin's minimum principle (PMP). This paper proposes an approach to develop a real-time strategy for battery/supercapacitor systems based on PMP and Energetic Macroscopic Representation without any need of adaptive mechanism for the co-state variable. Its performances are validated by simulation.

A medium-duty parallel Hybrid Electric Truck (HET) with Continuous Variable Transmission (CVT) is studied. The Energy Management Strategy (EMS) can be improved using a CVT compare to a classical gearbox because a new degree of freedom is introduced. However, the control and EMS is more complex. The Energetic Macroscopic Representation (EMR) is used to organize the model and deduce the control. A rules-based EMS is defined. Simulation results are provided.

Using supercapacitors (SCs) to configure the hybrid energy storage system (H-ESS) to extend battery life-time is promising for electric vehicles (EVs). Energy management strategy (EMS) is mandatory for such systems. Most of previous works develop improved EMS with the only one objective, normally on battery life-time. However, at least the costs on SCs operation also need to be taken into account. Generally, a methodology to develop multi-objective EMS is demanded. This paper presents a procedure to develop multi-objective EMS of H-ESS for an EV. SCs system losses are considered as the second cost function. Dynamic programming is used to give the benchmark in order to evaluate the performance of the other strategies. Simulation results validate the effectiveness of the developed off-line EMS. The dynamic programming generates a Pareto front to be used in order to compare with other on-line EMS.

A simulation tool is developed to study the energetic behavior of a subway system composed of several vehicles and Traction Power Substations (TPS). Such systems are complex to study due to the numerous subsystems in interactions. As an intermediary step, only two subways and one TPS, which are connected with a DC energy rail, are considered. Energetic Macroscopic Representation (EMR) is used to organize models and controls. An appropriate quasi-static model of the whole multi-train system is thus obtained. Simulation results analysis are provided.

Parallel Hybrid Electric Vehicles (HEVs) with Discrete and Continuous Variable Transmissions (DVT and CVT) are studied. A common Energetic Macroscopic Representation (EMR) is developed for both kinds of parallel HEVs. Then, a common control structure is deduced from this EMR. Energy Management Strategies (EMSs) are developed. Simulation results are provided and comparisons between Parallel HEVs with CVT and DVT are presented.

Nowadays energy storage is the keypoint of the development of electrical vehicles (EV) for charging time, autonomy and cost reasons. The main energy storage system for electrical vehicles is the battery and can cost up to one third of the vehicle price. Nevertheless the battery has limited power features and can be damaged by EV peak power requirements. Thus higher power density energy storage systems (such as supercapacitors) are used in combination with batteries (multisource EV). A reduced-scale EV demonstrator has been developed to present the concept of multi-source EV to high school and undergraduate students. The aim of this demonstrator is to highlight the interest of research on electric vehicle to attract students in this research topic.

In electric vehicles, supercapacitors (SC) are commonly used to perform a hybrid energy storage system (H-ESS). This approach, correctly coordinated and designed, can extend battery lifetime by limiting the battery current stress. SC are often coupled to DC/DC converters. To use the maximum energy stored in SC, high variability of the SC voltage is mandatory. Several time, the associated converter voltage ratio becomes too high and can produce instability of the system. Thus, at each time there is a minimal value for the SC voltage. This article proposes a dynamical limitation method for the SC voltage. The dynamic method is compared with a traditional constant limitation technique. Both are tested under the urban part of New European Driving Cycle with slope. The results point out that the dynamical limitation can ensure a better stability of the system regardless environment disturbance.

Organizing international conferences leads to significant amounts of emitted greenhouse gases (GHG’s). This is mainly due to the transport of the attendees to the conference venue. At IEEE-VPPC’14, actions were taken to reduce and to compensate the conference GHG emissions as well as to raise public awareness. This paper describes these actions and presents a quantitative estimation of the GHG sources related to the conference.

Energy management strategy (EMS) is the key for efficient hybrid vehicles. Two EMS kinds can be generally used: optimal-based algorithms to reach optimum and rule-based algorithms for its easy implementation. The paper objective is to propose a hybrid optimal EMS using optimal-based and rule-based approaches to use benefits of each approach. This hybrid optimal approach enables to reduce the computation time keeping the optimal behavior. This mix is realized thanks to a multi-level structuration of the EMS. This hybrid optimal EMS is a transient step to structure the EMS design. This hybrid optimal EMS, applied on a complex hybrid vehicle enables to divide the computation time by 16 keeping the optimal behavior.

Hardware-In-the-Loop (HIL) simulation of a simplified subway line is developed for experimental validation of subway line simulator. Energetic Macroscopic Representation (EMR) is used to organize models and controls. A subway supplied by a Traction Power Substation (TPS) through a DC energy rail is studied. The HIL simulation is based on the current control of an inductor, which reproduces the same behavior than the subway. A flexible and quasi-static model of the whole system is used and experimental results are provided.

In the automotive sector, Hardware-In-the-Loop (HIL) simulation is a useful step to develop new controls and energy management methods. We propose to develop a comprehensive and efficient full- scale power HIL simulation of a commercial electric vehicle using the graphical formalism of the Energetic Macroscopic Representation. This platform allows taking into account the limitations and component constraints at real power scale. After a validation step, we propose to modify the vehicle energy management to demonstrate the flexibility of the approach. Vehicle modifications may be validated in real time at the full-scale power.

Hardware-In-the-Loop (HIL) simulation of a simplified subway line is developed for experimental validation of subway line simulator. Energetic Macroscopic Representation (EMR) is used to organize models and controls. A subway supplied by a Traction Power Substation (TPS) through a DC energy rail is studied. The HIL simulation is based on the current control of an inductor, which reproduces the same behavior than the subway. A flexible and quasi-static model of the whole system is used and experimental results are provided.

In the automotive sector, Hardware-In-the-Loop (HIL) simulation is a useful step to develop new controls and energy management methods. We propose to develop a comprehensive and efficient full- scale power HIL simulation of a commercial electric vehicle using the graphical formalism of the Energetic Macroscopic Representation. This platform allows taking into account the limitations and component constraints at real power scale. After a validation step, we propose to modify the vehicle energy management to demonstrate the flexibility of the approach. Vehicle modifications may be validated in real time at the full-scale power.

Reduction of energy consumption in subway lines is necessary to promote cleaner intelligent transportation systems in urban city centers. Many technologies can be considered to achieve this goal, such as energy storage system (ESS) and/or Reversible Traction Power Substation (RTPS). Nevertheless, the complexity of such systems requires an accurate energetic simulation tool to evaluate the effectiveness of these solutions. This paper proposes thus a new simulation tool based on Energetic Macroscopic Representation (EMR), which allows an accurate estimation of energy consumption. Vehicles and Traction Power Substation (TPS) models are developed. Finally, a simple subway line is simulated under two conditions: with a classical power supply system using TPS, and with an innovative supply system using RTPS.

The energy management strategy is one of the key technologies for the design and development of hybrid electric vehicles (HEVs). In order to investigate the maximum potentials of various powertrain architectures and components in terms of fuel and emissions savings, an optimization for the energy management strategy is necessary. This paper will introduce one of the optimization-based energy management strategies, Dynamic Programming (DP). It is well known as it guarantees a global optimization of the power flow distribution between the combustion engine and the electric machines while taking into account the constraints of subsystems. In this paper, the principle of DP will be presented, and an application example in Peugeot 3008 Hybrid4 is given. The optimized strategy was simulated and analysis has been done based on the results with and without optimization. Even though DP is an off-line and non-causal optimization, it serves as a benchmark for comparison with the existing strategy. Thanks to DP, a rule-based strategy extracted from the DP optimization results is implemented and compared. This could be referred in the future strategy design.

In this paper, a multi Fuel Cell (FC) system is added to the Tazzari Zero Electric Vehicle. With a fixed amount of hydrogen, the influence of the number of FCs is studied by simulation according to a strategy that maximizes the use of the batteries. The vehicle range has been extended from 90 to 109.4 km, depending on the number of FCs. However, the distance drive with the H2 power is much more expensive than the equivalent distance with full electric power. A compromise between the full electric, the travel range and the system cost should define the final FC system’s architecture. The study has been done with a simulation tool by using the Energetic Macroscopic Representation.

Electric vehicle (EV) are one solution for the next decades to face the greenhouse gases emission issue. The most important drawbacks about the EV concern the limited range depending of the battery performances and the charging time. The vehicle range is estimated with standard drive cycles and ideal conditions. The objective of this paper is to propose a simulation tool to calculate the energy distribution in the EV including the thermal exchange between the heating system and the cabin. Indeed, the heating system (using thermal resistance) is an important energy consumer in the vehicle. All models are organized using Energetic Macroscopic Representation (EMR)

This paper deals with energy management for electric vehicle using SuperCapacitors (SCs) and battery. SCs are connected to the DC bus through a converter whereas battery is directly connected to the DC bus. Using the inversion-based rules of Energetic Macroscopic Representation (EMR), a systematic control structure can be deduced. Some differences can be shown in comparison with classical control schemes. This paper aims to compare a control scheme deduced from EMR and another control structure designed thanks to a more classical way. It can be noticed that some differences appear. As far as the structure is concerned, the number of sensor can be reduced in the EMR case. In terms of performances, some control errors appear in the classical scheme case.

In this paper, the traction system modeling of a commercial electric car is studied. Experimental data acquired during an on-road test drive are used to determine an efficiency map of the traction system. Using the deduced model, simulation results are compared to experimental results. The simulation tool using the proposed efficiency map method yields less than 5 % error on energy consumption compared to experimental test drive results.

In this paper the drive control of a commercial Electric Vehicle (EV) equipped with a low power Range Extender (RE) Fuel Cell (FC) system is studied. By using backstepping control, the drive control of the RE-EV is deduced and compared to the Inversion Based-Control deduced from its Energetic Macroscopic Representation. From the modelling, the backstepping defines the control structure and ensures the stability of a system regarding to Lyapunov-LaSalle theorems.

Organizing international conferences leads to emission of greenhouse gases (GHG). Even though, some conferences are devoted to “greener” systems (e.g. IEEE VPPC), the transport of attendees and the local organization of the conference are not “carbon free”. Consequently, some experiences are reported in this paper in order to reduce the ecological footprint of the conference itself and also to mitigate the emitted GHG for international congresses.

The aim of this paper is to propose an Energetic Macroscopic Representation (EMR) of the dynamic model of a traction power substation based on 6-pulse diode rectifier. This model is validated by comparing the wave forms with PSIM© software. Furthermore, it is applied to the energetic simulation of a subway line by combining the substation model with supply rail and vehicle models. This last part allows a good representation and comprehension of the real system.

This paper deals with inversion-based control of EVs with Hybrid Energy Storage System based on battery and supercapacitors. Using inversion rules of Energetic Macroscopic Representation (EMR), a systematic control structure can be deduced. However, it points out the possibility of an algebraic loop issue. Furthermore, it may result in computation problems. This paper aims to exhibit some solutions to avoid this problem in an efficient way.

This paper aims to study the influence of different system limitations on the energy consumption and the running time estimation of an automatic subway. These limitations take into account the maximal values of jerk, acceleration, torque and velocity. From a validated vehicle model and a Reference Velocity Generator (RVG), the impacts of these limitations are estimated. The main limitations are highlighted by simulations depending on the study objective. Some mechanical constraints can thus be neglected depending on the study.

The study of an electric vehicle is an attractive topic for students. At the University of Lille1 (France), an electric car is used to teach and develop drive control skills. From software simulation and Hardware-inthe- loop simulation, the students in electrical engineering learn drive control steps with a real electric vehicle. In this paper, the Energetic Macroscopic Representation is used to describe the electric car. This graphical tool allows the decomposition of the studied vehicle in accordance with physical laws. The control scheme is then deduced from the description using the inversion-based control rules.

The Hybrid4 PSA Peugeot Citroën architecture is one of the most complex HEV (Hybrid Electric Vehicle) in the market. This vehicle’s architecture is called double parallel HEV. The complexity of this technology makes its control complex. The objective of this paper is to highlight the different benefits of this architecture regarding different driving cycles. The Energetic Macroscopic Representation is used to describe and to deduce the systematic control.

In this paper the driving range of a commercial Electric Vehicle is extended using a low power fuel cell system. By using two driving cycles (Urban Driving Cycle (UDC) and a real cycle), both vehicles are compared in simulation using Energetic Macroscopic Representation. By adding a 1.2 kW fuel cell system and 2700 sl, 19.5 kg hydrogen tanks, the driving range is extended from 105.6 km to 128.2 km for an UDC, and from 68.3 km to 73.2 km for a real cycle.

Because it does not participate in the vehicle traction, the thermal energy is not highlighted in the electric and hybrid electric vehicle (EV and HEV) study, especially for electrical components like electric machines and batteries. Nevertheless, the thermal states of these components can have a great impact on the vehicle behaviour, such as safety, performances and autonomy, etc. This impact is more important if the driver turns on the heating system. In order to consider the thermal dimension of the energetic study for EV/HEV applications, a multiphysical modeling and description (for organizing this model with the energetic focus) of each component is required. This paper is focused on the multiphysical (electrical, mechanical and thermal) modeling and description of the electrical machine using EMR.

The aim of this paper is to determine an appropriate model of a hybrid diesel-electric locomotive in order to estimate its fuel consumption and test new energy managements. The locomotive is composed of a diesel-based generation subsystem, a battery – supercapacitors storage subsystem and a traction subsystem. A quasi-static model of the locomotive has been carried out from dynamical model. It allows the reduction of the computation time by 22 keeping an energy consumption accuracy of 99.4 %. Energetic Macroscopic Representation (EMR) is used as common description tool for the different models.

The aim of this paper is to compare different models of an automatic subway in order to determine the most appropriate of them for the evaluation of the energy consumption of different studied cases (normal mode and fault-modes). Several simplified models are then deduced from a reference dynamical model and are compared in term of accuracy and computation time. A quasi-static model with an equivalent single wheel is obtained and allows the reduction of the computation cycle by 708 compared to the dynamical model by keeping accuracy on the energy consumption of more than 99.3 % for a normal operating mode. By contrast, this model is not able to simulate correctly the system in fault-modes. This case requires a more complex model taking into account all the drives. Energetic Macroscopic Representation (EMR) is used to organize the different models.

The objective of this paper is to develop an energetic dynamical description of a model of an Internal Combustion Engine. This model is based on a simple power balance between input and output power of engine. The Energetic Macroscopic Representation (EMR) is used to organize the IC engine model. This energetic description will be coupled with the whole vehicle previously developed with EMR. The fuel consumption and the detailed power flow will be analysis for a complete drive cycle

During the development phase of a complex system like a Hybrid Electric Vehicle, different steps are done to develop the control and the energy management. Nowadays, only two steps are generally done: simulation and experimentation on the prototype vehicle. For complex system, a Hardware-In-the-Loop (HIL) simulation phase can be inserted between these two steps. In this paper, a HIL simulation of the Peugeot 3∞8 HYbrid4 vehicle is proposed. This vehicle has a double parallel architecture that makes the emulation complex. In order to structure this approach EMR (Energetic Macroscopic Representation) is used.

The EMR (Energetic Macroscopic Representation) of the traction system of a hybrid locomotive is presented. Different models are studied in order to be use for energy management of the entire system including energy storage subsystems. The simulation model is validated by comparison with experimental results.

This paper aims to compare a forward and backward simulation of the power propulsion system of an automatic subway. In the forward approach the control of the system is required. In the backward approach, no control is required but a derivative relationship has to be computed. Both simulations are compared in terms of accuracy of dynamical performances, maximal values of different variables and energy consumption and specifically when limitations occur.

This article deals with the consideration of thermal model for the evaluation of the energy consumption and losses of an ICE vehicle. The Energetic Macroscopic Representation (EMR) is used to organize this complex model of an ICE vehicle. This thermal representation has been validated by comparisons with other similar models.

This paper deals with the validation of the control structure of a double parallel Hybrid Electric Vehicle (HEV). Indeed, using inversion-based rules of Energetic Macroscopic Representation (EMR), a systematic control structure can be deduced. The objective of this paper is to test this control in the structural software of PSA Peugeot Citroën.

This article deals with several models for the estimation of electric consumption of an automatic subway. Backward and forward models are simulated. The forward simulation model is deduced from Energetic Macroscopic Representation (EMR). Different models are then compared in terms of accuracy and computation.

In recent times, an increased focus in the automobile sector has been to try and find reductions for emissions and fuel consump-tion using Hybrid Electric Vehicles (HEVs). Amongst the different HEV architectures, the most favorable is the series-parallel. This is because of its high performance and efficiency; as it joins the advantages of both series and parallel HEVs. In spite of its advantages, this system is more complex and intricate to model. Lying in the heart of this type of architecture is the Power Split Device (PSD), which has a vital role because of its power distribution. This paper aims to reduce the complexity of this system by providing a basic understanding of the differences between operating modes and power flows of the vehicle. Here, planetary gear is used to better understand the workings of this system.

Four French Grandes Écoles (Engineering and Business Schools) of PARISTECH open in October 2010 an education program which main objective is the impact study of the massive insertion of electrical energy in autonomous vehicles. The program with a common core curriculum and two different options is described.

Nowadays in the automobile sector, seeking reductions in emission and fuel consumption in Hybrid Electric Vehicles (HEVs) is an increased focus. The series-parallel HEV has an architecture that is more diverse than other types of HEVs as it joins both the advantages of series and parallel HEVs. One of the reasons that series-parallel HEVs are more complicated and complex is due to Power Split Devices (PSDs) such as the Ravigneaux geartrain. This complexity becomes more obvious in heavy-duty applications because of their high weight and power requirements. Modeling such PSDs becomes a vital point because of their role in power distribution, efficiency and enhanced design. In this paper, the modeling of these PSDs is conducted with the assistance of Energetic Macroscopic Representation (EMR) and implemented into MATLAB-Simulink®.

Various simulations of Electric Vehicles (EVs) or Hybrid Electric Vehicles (HEVs) are achieved for different objectives. In this paper, the influence of the electrical drive model is studied for simulation of an EV. Indeed, the electric machine with its associated converter can be modelled in three different ways: dynamic, static and quasi-static modelling. The studied electric machine is an induction machine. The aims of this paper are to show different effects of each model on an EV simulation and to study when each model should be used.

The energy storage is key issue for traction applications like Electric Vehicles (EVs) or Hybrid Electric Vehicles (HEVs). Indeed, it needs a higher power and energy density, a weak bulk and size, a long lifetime and a low cost. A hybrid Energy Storage System (ESS) using batteries and supercapacitors, seems to be a good device to answer to these constraints. The objective of the paper is to study the influence of control strategies for this hybrid ESS. Indeed, according to the used strategy, this association can be more and less interesting compared to an ESS only composed of batteries. Three control strategies are proposed.

In this paper a vehicle with the modelling of its tire-road interaction is described using two different energy-based graphical techniques: Power-Oriented Graphs (POG) and Energetic Macroscopic Representation (EMR). The main features of both approaches are presented and an integration between them is proposed: they can be used together to model different parts of the same system. Using the two techniques the whole vehicle can be represented with either a mathematical or a macroscopic view. From EMR an inversion-based control is given in order to control the vehicle velocity.

Nowadays in the automobile sector, seeking reductions in emission and fuel consumption in Hybrid Electric Vehicles (HEVs) is an increased focus. In different architectures of HEVs the most favourable architecture is a series-parallel HEV, because of its high operation modes and performance as it joins the advantages of both series and parallel HEVs. In spite of its advantages, this system is more complex and intricate to model. Lying in the heart of this type of architecture is the planetary gear which has a vital role because of its power distribution. This paper aims to reduce the complexity of the system with a modelling comparison of the planetary gear for a series-parallel HEV by both structural and functional approaches. In order to describe the two modelling approaches, Energetic Macroscopic Representation (EMR) is used for the functional approach and Simdriveline by MATLAB-SimulinkTM for the structural modelling approach. These two different topologies are shown and discussed through simulation results.

In this paper a vehicle with the modelling of its tire-road interaction is described using two different energy-based graphical techniques: Power-Oriented Graphs (POG) and Energetic Macroscopic Representation (EMR). The main features of both approaches are presented and an integration between them is proposed: they can be used together to model different parts of the same system. Using the two techniques the whole vehicle can be represented with either a mathematical or a macroscopic view. From EMR an inversion-based control is given in order to control the vehicle velocity.

Various simulations of Hybrid Electric Vehicles (HEVs) are achieved for different objectives. But, all components are not always taken into account for their complexity and their computation time. In this paper, the influence of the clutch model is studied for simulation of a parallel HEV. Indeed, the clutch is a difficult element to model. Two simulations are provided, with and without the clutch. The effects on the fuel consumption and on the dynamic performance are studied.

In this paper a vehicle is described using two different energetic graphical techniques: Power-Oriented Graphs (POG) and Energetic Macroscopic Representation (EMR). As these techniques have different features and purposes, they can be used together to model different parts of the same system. The POG technique is used to model the interaction between tire and road in order to have a dynamic energetic model, while the EMR technique is used to represent the whole system and deduce the control structure through the inversion-based methodology. Thanks to the use of both techniques the whole vehicle can be represented and a structure to control the vehicle velocity is given.

A double parallel Hybrid Electric Vehicle (HEV) is studied using Energetic Macroscopic Representation (EMR). This graphical description enables an inversion-based control scheme of this complex HEV. A first energy management is provided.

This paper presents a methodology to design the control part of a Fuel Cell (FC) stack. Here, the objective is to control the FC voltage. This methodology is based on Energetic Macroscopic Representation (EMR) of the FC and leads to a so-called Maximal Control Structure (MCS). The MCS is a step by step inversion of EMR (inversion model based control structure). The control design process is based on an explicit definition of the problem. In fact, as examples, the tuning inputs, the system objectives or constraints are highlighted to organize the control. Moreover, the MCS shows the places where sensors are necessary and the controller which are requested. Unfortunately, MCS is only a theoretical control structure. Consequently, a realistic structure needs some simplifications that lead to a so-called Practical Control Structure (PCS). The FC model is here presented and experimentally validated. The designed control structure is simulated and results are discussed.

This paper deals with the identification of a new high power starter-alternator system, using both: a Finite Element Method (FEM) modeling and an elementary experimental vector control. The drive is composed of a synchronous 7-phase claw-pole machine supplied with a low voltage / high current Voltage Source Inverter (VSI). This structure needs specific approaches to plan its electrical and mechanical behaviors and to identify the parameters needed for control purpose. At first, a Finite Element Method (FEM) modeling of the machine is presented. It is used for the predetermination of the electromotive forces and of the torque. Experimental results are in good accordance with numerical results. In a second part, resistive and inductive parameters of the drive are determined by an original experimental approach that takes into account each component of the drive: the battery, the VSI and the machine.

This paper deals with the identification of a new high power starter-alternator system, using both: a Finite Element Method (FEM) modeling and an elementary experimental vector control. The drive is composed of a synchronous 7-phase claw-pole machine supplied with a low voltage / high current Voltage Source Inverter (VSI). This structure needs specific approaches to plan its electrical and mechanical behaviors and to identify the parameters needed for control purpose. At first, a Finite Element Method (FEM) modeling of the machine is presented. It is used for the predetermination of the electromotive forces and of the torque. Experimental results are in good accordance with numerical results. In a second part, resistive and inductive parameters of the drive are determined by an original experimental approach that takes into account each component of the drive: the battery, the VSI and the machine.

This paper deals with the modeling and the control of a new high power 12V starter-alternator system. The drive is composed of a 7-phase synchronous claw-pole machine with separate excitation, supplied with a 7-leg Voltage Source Inverter (VSI) designed for low voltage and high current. The system is modeled in a generalized Concordia frame and a graphical description is used to highlight energetic properties of such a complex system. A control scheme is then deduced from this graphical description. Two controls are achieved in generator mode: one is using the VSI in a square-wave mode, the other in a Pulse Width Modulation (PWM) mode. Experimental results are provided.

This paper presents power sources models for Hybrid Electric Vehicles (HEV). These models are designed in order to be integrated in a complete HEV simulation. Moreover, the final objective of this simulation is to study two control levels: the local control of each subsystems and the energy management of the entire system. Consequently, a multi-physics control oriented formalism is used: Energetic Macroscopic Representation (EMR).

This paper focuses on an experimental method to determine the electric parameters of a seven-phase low-voltage multiphase drive. The drive is a belt driven starter-alternator for powerful cars with Hybrid Electrical Vehicles (HEV) functions. The resistive and inductive parameters are necessary to obtain the six characteristic time constants of the control modeling. Classical direct measurements lead to imprecise results because of very low values for the windings electric resistance and inductance. Effects of the imprecision on the measurements are all the more important that time constants are obtained by a ratio of cyclic inductances by resistance, with cyclic inductances being a linear combination of seven measured inductances. The methodology for identification detailed in this paper is based on a stator current vector control, in a multi-reference frame. This methodology allows us to get directly these time constants. Numerous measurements allow the robustness of the method to be evaluated.

Abstract - In this paper the traction system of an automatic subway is described using four different energetic graphical techniques: Bond-Graph (BG), Energetic Macroscopic Representation (EMR), Power-Oriented Graphs (POG) and Vectorial Bond-Graph (VBG). The aim of this paper is to highlight the analogies and the differences between these modelling techniques in the analysis and simulation of the considered system.

This paper focuses on an experimental method to determine the electric parameters of a seven-phase low-voltage multiphase drive. The drive is a belt driven starter-alternator for powerful cars with Hybrid Electrical Vehicles (HEV) functions. The resistive and inductive parameters are necessary to obtain the six characteristic time constants of the control modeling. Classical direct measurements lead to imprecise results because of very low values for the windings electric resistance and inductance. Effects of the imprecision on the measurements are all the more important that time constants are obtained by a ratio of cyclic inductances by resistance, with cyclic inductances being a linear combination of seven measured inductances. The methodology for identification detailed in this paper is based on a stator current vector control, in a multi-reference frame. This methodology allows us to get directly these time constants. Numerous measurements allow the robustness of the method to be evaluated.

Abstract – In this paper the friction clutch of a vehicle is modelled using three special graphical tools which are developed to model power flow through physical systems: energetic macroscopic representation, power oriented graph and bond graph. Due to its non-linear behaviour, the modelling of the clutch is a challenging point. Indeed, it connects or disconnects mechanical parts, which can have similar or diverging rotation speeds. The aim of the paper is to highlight the features of each tool for the clutch modelling, the simulation and the analysis of such systems including non-linearities.

Abstract - In this paper the traction system of an automatic subway is described using four different energetic graphical techniques: Bond-Graph (BG), Energetic Macroscopic Representation (EMR), Power-Oriented Graphs (POG) and Vectorial Bond-Graph (VBG). The aim of this paper is to highlight the analogies and the differences between these modelling techniques in the analysis and simulation of the considered system.

An innovative subway without supply rail is presented. This article deals with the sizing of the required onboard energy between two stations in the worst case. The influence of the system limitations on this sizing is studied. It shows the importance of the system limitations to design the energy storage subsystem.

In this paper a new-anti-slip control is proposed for the traction system of an automatic subway. Energetic Macroscopic Representation was used to proposed a graphical and physical description of the whole traction system. An inversion based control is deduced from this graphical description. This control scheme highlights different possibilities of control. A new anti-slip strategy is then deduced from the inversion-based control. Before an implementation on an actual vehicle, the new control is validated on a reduced power experimental set-up. A hardware-in-the-loop simulation is thus used to asses performance of this control in the same conditions as in the actual vehicle. Experimental results are provided.

The Energetic Macroscopic Representation (EMR) has been developed in 2000 to develop control of systems with several drives. Since 2002 this graphical tool has been introduced to teach drive control in France, then Canada and Switzerland. The University of Lille proposes two drive control units for students in electrical engineering: initiation level and expert level unit. This first paper deals with the content of the initiation level unit and describes the simulation project of an electrical vehicle using EMR.

This paper presents a model of a fuel cellsupercapacitor system which represents the electric power supply device of a Hybrid Electric Vehicle (HEV). The fuel cell and the supercapacitors are coupled with a DC bus and a common cooling system. The first part of this paper deals with the modeling of the elements of the system (fuel cell system (FCS), supercapacitors, power electronics, and temperature regulation system). The second part deals with the design of a control structure which regulates the DC bus voltage, the fuel cell power, and the power source temperature. Simulation and experimental results are provided and analyzed.

Dual-drive gantry systems are commonly used in many industrial applications. However, as few papers are available in the literature, this kind of system is difficult to broach. Based on an energetic approach so-called Energetic Macroscopic Representation (EMR), this paper presents a graphical modelling based on lumped-parameters. The initial drive is decomposed into a set of decoupled fictitious systems using a mathematical transformation. Since the modelling respects the integral causality, inversion-based controls are thus deduced. More generally, this approach proposes a way to analyze and deduce models and controls of multi-drive mechatronic systems.

Abstract – A Hardware-In-the-Loop (HIL) simulation of a convention vehicle system is developed for experimental validations of clutch modelling. Two different states have to be taken into account: clutch locked and slipping. Two different models are then used and a specific condition defines the commutation between both models with respect to the physical energy flow. Energetic Macroscopic Representation (EMR) is used to organize the numerous blocks required. A Petri net is employed to activate a model according to clutch state (lock and slip). The HIL is based on a controlled IM drive, which imposes the same behaviour of the mechanical powertrain to the clutch. A flexible and dynamical model of the whole system is used and simulation results are provided with regard of the experimental results.

A Hardware-In-the-Loop (HIL) simulation of the traction system of automatic subway VAL 206 is developed for experimental validations of new control strategies. Energetic Macroscopic Representation is used to organize the numerous blocks required. The HIL simulation is based on two vector-controlled induction machines, which impose the same behavior of the mechanical power train to the traction drives. A flexible and dynamical model of the whole system is used and experimental results are provided.

Abstract – A Hardware-In-the-Loop (HIL) simulation of a convention vehicle system is developed for experimental validations of clutch modelling. Two different states have to be taken into account: clutch locked and slipping. Two different models are then used and a specific condition defines the commutation between both models with respect to the physical energy flow. Energetic Macroscopic Representation (EMR) is used to organize the numerous blocks required. A Petri net is employed to activate a model according to clutch state (lock and slip). The HIL is based on a controlled IM drive, which imposes the same behaviour of the mechanical powertrain to the clutch. A flexible and dynamical model of the whole system is used and simulation results are provided with regard of the experimental results.

A Hardware-In-the-Loop (HIL) simulation of the traction system of automatic subway VAL 206 is developed for experimental validations of new control strategies. Energetic Macroscopic Representation is used to organize the numerous blocks required. The HIL simulation is based on two vector-controlled induction machines, which impose the same behavior of the mechanical power train to the traction drives. A flexible and dynamical model of the whole system is used and experimental results are provided.

A hybrid energy storage system has been proposed using supercapacitor and compressed air in order to store energy from photovoltaic panels. A simulation model is developed using Energetic Macroscopic Representation. Such a description can be used to deduce new control laws of the hybrid storage system using specific inversion rules. The simulation model is validated by comparison with experimental results.

This paper presents a model of a whole polymer electrolyte fuel cell system including the stack, an air compressor, a cooling system and a power electronics converter. This model allows the integration in a model of a complete hybrid electric vehicle. The level of detail of the model is chosen to enable control rules design, ancillaries sizing and study of the interaction between the elements of the vehicle. This model is formalized with Energetic Macroscopic Representation (EMR). Thus the model is organized in a unified multi-domain graphical description. Experimental results are compared to simulations for validation of the model accuracy.

A hybrid energy storage system has been proposed using supercapacitor and compressed air in order to store energy from photovoltaic panels. A simulation model is developed using Energetic Macroscopic Representation. Such a description can be used to deduce new control laws of the hybrid storage system using specific inversion rules. The simulation model is validated by comparison with experimental results.

In the context of high power low-voltage applications as starter-generator for automotive, multi-phase drives present the attractive characteristic of reducing the current per phase and per leg. A 5- or 7-phase machine is also more suitable for using concentrated windings, attractive for their short end-windings and subsequently for a higher expected torque-to-volume density. In this perspective, the 5- and 7-leg Voltage Source Inverters (VSI) are compared with the 3-leg VSI. In the first part, for the same set of resistances and inductances coupled in different wye-coupling configurations, we examined the DC-bus currents and the power recovered by the load for a square-wave VSI control: the 7-leg VSI is the more efficient because it makes best use of the harmonics. In the second part, the torque ripples of 3-, 5- and 7-phase drives are compared: the 7-phase drive torque ripples are the lowest ones because of the less sensitivity to the harmonics of the currents. In the last part, a Pulse Width Modulation control is studied, with almost the same voltage harmonics amount as this one obtained with the square-wave mode control. Experimental results are given for the 7-leg VSI either with a passive load or with a 7-phase permanent magnet synchronous motor.

The French national MEGEVH project deals with energy management of hybrid electric vehicles (HEV). The objective is to provide general methodologies to model HEV and optimize their energy flows. The project is subdivided in modeling and optimization sub-projects. Graphical modeling has been chosen to highlight energetic properties of the studied vehicles. Two actual vehicles have been taken as reference for the developments. Theoretical methods will be firstly developed independently of the kind of HEV. Then these methods will be tested on the reference vehicles. The MEGHEV objectives and organization are firstly detailed. In a second section, Energetic Macroscopic Representation of a parallel HEV is described as an example of use of graphical modeling for energy management

Abstract – The studied storage system is composed of a supercapacitor bank and a brake resistor which acts when supercapacitor is full. Moreover the supercapacitor has a series resistor which influences the energetic efficiency. In this paper, three control strategies are presented for a traction application. Two strategies maximize the charge of supercapacitor to increases efficiency. Energetic Macroscopic Representation (EMR) is used to organize the numerous blocks required for modeling and control. Experiment results are provided.

This paper deals with control in fault operation of a seven-phase Permanent Magnet Synchronous Machine supplied by a seven-leg Voltage Source Inverter (VSI). Using a Multi-Machine description, a seven-phase machine which presents a special ability to be controlled with only five phases supplied has been designed. The machine is presented and experimental results are provided when two phases are opened. In a first case of no change of classical control, high torque ripples are observed. In a second case, a specific control deduced from the Multi-Machine modelling is suggested for reducing torque ripples.

Abstract – A Hardware-In-the-Loop (HIL) simulation of a wind energy conversion system has been developed using Energetic Macroscopic Representation. Wind, turbine and mechanical power train are emulated by controlled DC drive to impose the dynamical behavior of the actual process on the generator shaft. In this paper, this HIL simulation is extended to two different wind turbines. The first one leads to extract a rated power of 900 kW using fixed blades. The second turbine leads to extract a rated power of 2 MW using adjustable blades. Experimental results are provided on reduced power experimental set-up for both wind turbines.

Abstract – A Hardware-In-the-Loop (HIL) simulation of a wind energy conversion system has been developed using Energetic Macroscopic Representation. Wind, turbine and mechanical power train are emulated by controlled DC drive to impose the dynamical behavior of the actual process on the generator shaft. In this paper, this HIL simulation is extended to two different wind turbines. The first one leads to extract a rated power of 900 kW using fixed blades. The second turbine leads to extract a rated power of 2 MW using adjustable blades. Experimental results are provided on reduced power experimental set-up for both wind turbines.

Abstract – A Hardware-In-the-Loop (HIL) simulation of an electric vehicle traction system is developed for experimental validations of electrical drives. Energetic Macroscopic Representation is used to organize the numerous blocks required. A classical 2-driven-wheels traction is studied with an induction machine. The HIL is based on a controlled DC drive, which imposes the same behavior of the mechanical power train to the induction machine. A flexible and dynamical model of the whole system is used and experimental results are provided.

Properties of the travelling Wave Ultrasonic Motor (TWUM)-among which we find a high-torque to mass ratio, locking without supply, ultrasonic operation - are very attractive for embedded application, such as human prothesis for example. But unfortunately, its control for high precision or high dynamic motion is not easy to achieve because of many non linearities induced by its particular energy conversion process. This is why this paper deals with the modelling of a TWUM, based on a physical causal approach. According to the inversion principle, control strategies are deduced as well as a novel torque estimation structure. A mechanical claw control using this torque estimator is then achieved and experimental results check the accuracy of the proposed control scheme.

Abstract – The modeling of a clutch in a powertrain transmission is a sensitive issue because of its non-linear behavior. Two different states have to be taken into account: clutch locked and slipping. Two different models are then used and a specific condition defines the commutation between both models with respect to the physical energy flow. An application to parallel Hybrid Electric Vehicles (HEV) is then presented. Energetic Macroscopic Representation (EMR) is used to organize the numerous blocks required. A Petri net is employed to activate a model according to clutch state (lock and slip).

A simulation model of the whole traction system of subway VAL 206 is developed using the Energetic Macroscopic Representation (EMR). This traction system is composed of 6 choppers, 4 DC machines, 4 bogies and 8 wheels. Non-linear devices of the mechanical power train are taken into account. The whole traction system is simulated using Matlab-SimulinkTM. A validation of this model is provided in comparison with ex-perimental results obtained from the actual process. This whole model can now be used to develop more advanced controls of VAL 206.

Abstract – The storage system in this paper is made of supercapacitors. The main goal is to ensure an efficient energy management in a series hybrid vehicle, even if braking resistors are still needed. Design considerations are discussed. In particular the influence of the inductor resistance on the system stability is described. A Maximum Control Structure is then deduced from the Energetic Macroscopic Representation of the storage system. Comparisons between experimentation and simulation are presented in order to highlight the influence of the inductor resistor. Experiments are then carried out on a normal operating cycle.

Dresden , Germany, 11-14 september 2005, CD-ROM.

In this paper the traction system of an automatic subway is described using several graphical tools: transfer functions, bond-graph, causal ordering graph, power flow diagram and energetic macroscopic representation. The aim of the paper is to highlight the interest of each tool for the analysis and the control of such a system.

A multi-machine multi-converter system formalism has been proposed in order to describe systems composed of several electrical machines and converters. The keys of such systems are coupling devices, which have to distribute energy. Control structures have also been suggested according to an inversion principle. The inversions of coupling devices have been made using repartition and weighting criteria. In this paper, systems with several coupling are studied. Several control structures can be found. One of them leads to shift some control blocks and to merge the repartition and weighting blocks. A railway traction system is given as example.

A multi-machine multi-converter system formalism has been proposed in order to describe systems composed of several electrical machines and converters. The keys of such systems are coupling devices, which have to distribute energy. Control structures have also been suggested according to an inversion principle. The inversions of coupling devices have been made using repartition and weighting criteria. In this paper, systems with several coupling are studied. Several control structures can be found. One of them leads to shift some control blocks and to merge the repartition and weighting blocks. A railway traction system is given as example.

Continuous processes in the paper, plastics, textile and other industries, require several drives working in synchronism. Regulation of the mechanical tension in the material is a prime quality criterion. We propose strategies and a control structure that incorporate an active dancer roll in a rewinder system to improve performance of the tensioning loop to disturbances such as voltage supply fluctuations. The linear actuator is used to close a tension loop, the adjoining nip stage maintains the linear actuator close to its mid range of operation and the winder roll is velocity controlled. The effects of voltage variations on the flux observer in the variable speed drives and on loss of performance of the induction motor drives are highlighted. The results show the potential of the proposition as a retrofit option to reduce sensibility to voltage sags in winding systems with little modification to the actual controllers.

Abstract – The main problem with Hybrid Electric Vehicles (HEV) is the management of batteries. We suggest to replace the batteries by an energy storage system made of supercapacitors on a series HEV with two traction drive. A Maximum Control Structure (MCS) of such an HEV is presented to organize the control of the different subsystems. MCS is based on specific inversion rules of Energetic Macroscopic Representation (EMR). This methodology leads to a global model of the system and its deduced control. Moreover, this enable to identify precisely the maximum control for the chopper associated with the supercapacitors. The simulation of an Extra Urban Driving Cycle (EUDC) is provided.

IAS 2004, IEEE Industrial Application Society Annual Meeting, Seattle, Washington October 3-7, 2004, CD-ROM

The Energetic Macroscopic Representation is used to define the control of the traction system of subway VAL 206. A theoretical maximum control structure is deduced from this modelling using inversion rules. A practical control structure is then obtained by simplifications.

The traction system of the subway VAL 206 is ensured by DC machines connected in series. A common chopper supplies the armature windings and a double-chopper supplies the field windings. Another power structure is suggested in order to increase performances during losses of adhesion. A specific control strategy is defined in order to obtain different torque on both machines despite their common armature current. An anti-slip control can thus be developed in applying the desired torque to each bogie at just the right time. This torque tracking strategy is validated on a 1.5 kW experimental set-up.

PESC 2004, IEEE Power Electronics Specialists Conference, Aachen, Germany in June 20 - 25, 2004,CD-ROM.

Abstract – The simulation of a series HEV (hybrid electric vehicle) is suggested by using the Energetic Macroscopic Representation (EMR). Simplified models are used in a first step. They lead to the simulation of an overall HEV with its control. The system is decomposed in two parts: the charge and traction subsystems. Simulations with Matlab-SimulinkTM are provided for the simplified system. These first simulations can now be improved by using more complex models of some devices. Indeed, the EMR organizes systems as interconnected components, that leads to modularity and flexibility.

The paper presents a method for structuring a scalable model of a permanent magnet synchronous machine in a manner that facilitates its integration into system-level simulations. This is achieved by utilizing the energetic macroscopic representation formalism to organize the equations of the scaling laws. The model comprises a fixed reference permanent magnet synchronous machine model that is complemented with two electrical and mechanical power adaptation elements to ensure scalability. Three scaling choices are analyzed, and the findings reveal that the equations for the power adaptation elements differ based on the selected scaling choice.

– Aujourd’hui, pour faire face au réchauffement climatique et minimiser l’impact des Gaz à Effet de Serre (GES), de nouvelles règlementations européennes plus strictes apparaissent. Dans le domaine automobile, elles concernent notamment les cycles normalisés de conduite pour les tests de véhicule sur banc à rouleau. L’objectif de cet article est de montrer l’impact énergétique de la réglementation européenne 2018/1832 concernant la procédure WLTP (procédure d'essai mondiale harmonisée pour les voitures particulières et véhicules utilitaires légers) au travers de simulations énergétiques. L’une des règlementations impose une vitesse qui doit être comprise dans une plage de variation de plus ou moins 2 km/h par rapport à la vitesse de référence du cycle WLTC classe 3. Cette plage de variation de vitesse a pour conséquence d’impacter en moyenne 1,61 % la consommation du véhicule électrique. Les simulations ont été réalisées en utilisant le formalisme REM (Représentation Energétique Macroscopique) appliqué sur la Renault ZOE.

La réduction de la consommation énergétique dans tous les domaines (automobile, industrie, habitation…) est une nécessité écologique et économique. Les pertes énergétiques, issues de différents phénomènes (résistance, frottement…) se manifestent dans la quasi-totalité des cas par un dégagement de chaleur. La valorisation de cette chaleur, si elle est en quantité suffisante, peut être une solution pour réduire la consommation d’énergie globale du système. Le générateur thermoélectrique est un convertisseur utilisant l’effet Seebeck pour convertir l’énergie thermique en énergie électrique. L’objectif de cet article est de modéliser et simuler ces modules. Une validation utilisant les données constructeurs sera également présentée. Les modèles seront organisés en fonction du formalisme R.E.M. (Représentation Energétique Macroscopique) afin de déduire, ultérieurement, une structure de commande de ces modules et de les coupler aux systèmes déjà organisés avec cet outil de représentation.

De nombreux systèmes utilisent plusieurs entraînements électromécaniques, c’est à dire une répartition de l’énergie sur plusieurs chaînes de conversion. Les divers actionneurs sont alors de dimensions réduites et les contraintes sur les divers éléments sont plus faibles que pour un actionneur unique. La disponibilité et la fiabilité de l’ensemble sont ainsi augmentées. De plus, lors d’une mise en défaut d’une composante, un fonctionnement en marche dégradée est souvent possible. Mais ces systèmes demandent une commande plus complexe des divers entraînements. Par ailleurs, les diverses chaînes de conversions se perturbent les unes les autres, ce qui peut occasionner des dysfonctionnements, voire des détériorations. Ces systèmes, utilisés depuis de nombreuses années dans l’industrie, ont d’abord été considérés comme des ensembles d’entraînements indépendants. Leur commande a alors été composée d’entités séparées. Mais les diverses contraintes inhérentes à cette distribution d’énergie ont dû être prises en compte, ce qui a été réalisé progressivement, au cas par cas. Un groupe national de réflexion a été organisé en 1998 dans le cadre du GdR SDSE, afin d’étudier ces systèmes, ce qui a mené à la dénomination de Systèmes Multimachines Multiconvertisseurs (SMM). Les éléments clefs de la répartition d’énergie ont été définis comme éléments de couplage, reliant plusieurs chaînes de conversion. Cette démarche commune, si elle s’intéressait à des systèmes déjà connus, a débouché sur une nouvelle vision de ces systèmes et de leur gestion. Les études qui ont suivi, allaient le prouver, avec le développement de structures particulières, d’analyses spécifiques, et de lois de commandes originales. A l’heure actuelle, la démarche classique d’étude des SMM est liée à une approche réductionniste : l’étude du système se déduit directement de celle de ses composantes. Mais les SMM ne peuvent pas se résumer à une association simple de machines et de convertisseurs. Ce concept est à l’origine de l’approche systémique entreprise dans nos travaux : les associations des composantes ont un impact sur l’ensemble. Le L2EP a utilisé cette approche systémique pour développer une démarche de structuration de la commande des tels systèmes. Ces travaux ont abouti à la Représentation Energétique Macroscopique (REM) dont la notion centrale est alors l’énergie. Cette vision souligne les manipulations d’énergie de tels systèmes. Les commandes déduites correspondent alors à une gestion optimisée de l’énergie au plus près des éléments qui la transforment. Afin de situer le travail proposé, le premier chapitre fait un bref récapitulatif des modélisations et commandes des systèmes électromécaniques. Le deuxième chapitre est consacré à la REM, outil de description synthétique des systèmes électromécaniques. Une Structure Maximale de Commande (SMC) se déduit naturellement de la REM à l’aide de règles d’inversion. Les divers concepts de REM et de SMC sont illustrés au chapitre III à l’aide d’un exemple issu d’applications pratiques : de la modélisation de ses composantes à la commande en temps réel (plate-forme expérimentale SMM du L2EP). Le dernier chapitre ouvre une discussion sur les améliorations du formalisme et sur son extension à d’autres applications.

Kyenote in Plenary session

Causal Ordering Graph and Energetic Macroscopic Representation are graphical descriptions to model electromechanical systems using integral causality. Inversion rules have been defined in order to deduce control structure step-by-step from these graphical descriptions. These two modeling tools can be used together to develop a two-layer control of system with complex parts. A double-drive paper system is taken as an example. The deduced control yields good performances of tension regulation and velocity tracking.

Some traction systems are composed of machines connected in series or in parallel. The studied system is composed of two DC machines with armature windings connected in series. Three choppers are used: one for the armature windings and one for each field winding. In industrial cases, such drives are controlled with a master slave strategy: only one machine is really controlled. The behaviour of the slave machine is imposed by the master machine. This paper suggests a new control strategy for such drives. Each machine is really controlled in spite of the common armature current. This strategy enables different rota-tion speeds for curves. Experimental results are provided.

Les transports routiers utilisant l’énergie fossile sont responsables d’une partie des gaz à effet de serre. Le véhicule hybride représente une solution à court et moyen terme pour diminuer ces émissions. En revanche, la complexité de leur constitution (multiplicité des sources et des conversions d’énergie) requiert une approche systémique pour les optimiser. Dans cet article les différents types de véhicules hybrides sont d’abord présentés. L’organisation de leurs modèles et commandes est ensuite introduite. La dernière partie se focalise sur la gestion de l’énergie avec un tour d’horizon des méthodes utilisées depuis celles basées sur des règles intuitives jusqu’aux plus évoluées.

La représentation énergétique macroscopique (REM) est un formalisme graphique pour la représentation synthétique de systèmes énergétiques multidisciplinaires. La REM conduit à une description fonctionnelle d’un système énergétique. Elle respecte la causalité intégrale du système étudié, ce qui permet d’en déduire de façon systématique une structure de commande. L’objectif de cet article est de présenter les fondements de la REM et de les appliquer sur un exemple : un ascenseur à traction électrique.