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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.

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 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

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

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

High cost, no-ideal driving range and charge time limit electric vehicle market share. Facing these challenges, an integrated motor drive/battery charger system has been proposed by Valeo. A further advancement, based on this system, is present in this paper; for the first time, the integration of traction, charging and air-compressor supply modes is proposed and tested by real-time experimentation. This integrated system is expected to increase the vehicle component compactness and power, therefore potentially reduce the cost and battery charging time. An overall and unique control scheme is detailed to achieve the three main operating modes: traction, charging and air-compressor supply modes. The real-time experimentation results show the system feasibility.

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 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.

(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.

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.

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.

This paper presents the modeling and control of an Electric Vehicle (EV) driven by a 5-phase Permanent Magnet Synchronous Machine (PMSM). The machine in an open-end winding configuration is supplied by two isolated 5-leg Voltage Source Inverters (VSIs). The inverters are fed by a Hybrid Energy Storage System (HESS) consisting of a battery and Supercapacitors (SCs). To increase the battery lifetime, the SCs are used to provide the high-power requirement during driving operations. In addition, an Energy Management Strategy (EMS) is proposed to take advantages of this EV architecture. Numerical results are derived to verify workability of the EV system.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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).

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.

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.

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.

Global warming requires fast developments and deployments of electrified vehicles to reduce the ecological footprint of transportation. Waiting for both battery and fuel cell electric vehicles to fully mature, intermediate solutions to electrify the internal combustion engine-powered vehicles, such as Hybrid Electric Vehicles (HEV), have been developed during the last decades. This synthesis report is devoted to the structuration of real-time control algorithms for HEV using a systemic approach. It consists of an overview of my research activities during the last fifteen years at the L2EP (Laboratory of Electrical Engineering and Power Electronics of Lille) of the University of Lille. These activities deals with the organization at both local and global control of HEV independently of powertrain topologies and energy storage systems. To make easier the understandability of the dynamic interaction of complex systems, the Energetic Macroscopic Representation (EMR) formalism has been utilized along all my research activities in both top-down and bottom-up approach. Most of my activities have furthermore contributed to the French collaborative network MEGEVH, which aims to foster collaborations between academic institutions and industrial partners on energy modelling and energy management for electrified vehicles. In this way, the first chapter introduces the context of the research activities. Subsequently, the second chapter discusses on the stability problematics of the inversion-based control deduced from EMR. The third chapter deals with two different decomposition approaches of real-time global control of HEV while the fourth chapter details experimental validations using EMR for HEV. Perspectives for the coming years are drawn at the end of the report.

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.

Résumé – La résolution du problème de pollution est l’un des défis du XXIème siècle. Ces dernières années ont vu un développement important de Véhicules Électriques Hybrides (VEHs) qui allient les avantages des propulsions thermique (autonomie) et électrique (faible pollution). Le système embarqué est de plus en plus complexe car il multiplie les éléments de conversion énergétique ainsi que les couplages. L’objectif de ce travail est de proposer une méthodologie d’étude de VEHs pour en déduire des règles de commande (gestion locale de l’énergie) et de stratégie (gestion globale de l’énergie). Nous avons utilisé la Représentation Énergétique Macroscopique (REM), qui décrit de manière synthétique des systèmes complexes et leur commande, basée sur le principe d’action et de réaction des éléments connectés. Trois types de véhicules ont ainsi été étudiés, les architectures hybrides série, parallèle et mixte. La REM permet de mettre en avant les noeuds énergétiques des VEHs étudiés. En se basant sur l’exploitation des contraintes et propriétés énergétiques des sous systèmes associés, l’inversion de ces couplages fait apparaître, au sein de la structure de commande locale, les divers degrés de liberté qui mènent à l’articulation de la gestion globale de l’énergie des architectures étudiées. De part la complexité et la multidisciplinarité des véhicules hybrides, ce travail a également participé à l’extension des travaux de formalisme pour la commande et la gestion d’énergie des systèmes à énergies réparties. De nombreux travaux sont en cours et restent à faire pour développer ce type de véhicule.