Дисертації з теми "Véhicules électriques – Design – Consommation d'énergie"
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Aroua, Ayoub. "Mise à l'échelle des entraînements électromécaniques pour la conception au niveau système dans les premières phases de développement des véhicules électriques." Electronic Thesis or Diss., Université de Lille (2022-....), 2023. http://www.theses.fr/2023ULILN042.
The automotive industry is required to accelerate the development and deployment of electrified vehicles at a faster pace than ever, to align the transportation sector with the climate goals. Reducing the development time of electric vehicles becomes an urgent priority. On the other hand, the industry is challenged by the increasing complexity and large design space of the emerging electrified powertrains. The existing approaches to address component design, such as numerical methods exemplified by finite element method, computational fluid dynamic, etc., are based on a detailed design process. This leads to a long computational burden when trying to incorporate them at system-level. Speeding up the early development phases of electrified vehicles necessitates new methodologies and tools, supporting the exploration of the system-level design space. These methodologies should allow for assessing different sizing choices of electrified powertrains in the early development phases, both efficiently in terms of computational time and with reliable results in terms of energy consumption at system-level. To address this challenge, this Ph.D. thesis aims to develop a scaling methodology for electric axles, allowing system-level investigation of different power-rated electric vehicles. The electric axle considered in this thesis comprises a voltage source inverter, an electric machine, a gearbox, and a control unit. The scaling procedure is aimed at predicting the data of a newly defined design of a given component with different specifications based on a reference design, without redoing time and effort-consuming steps. For this purpose, different derivations of scaling laws of the electric axle components are thoroughly discussed and compared at component-level in terms of power loss scaling. A particular emphasis is placed on examining the linear losses-to-power scaling method, which is widely employed in system-level studies. This is because, this method presents questionable assumptions, and has not been the subject of a comprehensive examination. A key contribution of the presented work is the derivation of power loss scaling laws of gearboxes, which has been identified as a gap in the current literature. This is achieved through an intensive experimental campaign using commercial gearboxes. To incorporate the scaling laws at system-level and study the interaction between the scaled components, the energetic macroscopic representation formalism is employed. The novelty of the proposed method lies in structuring a scalable model and control for a reference electric axle to be used in system-level simulation. The novel organization consists of a reference model and control complemented by two power adaptation elements at the electrical and mechanical sides. These latter elements consider the scaling effects, including the power losses. The methodology is applied for different study cases of battery electric vehicles, ranging from light to heavy-duty vehicles. Particular attention is paid to assessing the impact of the linear power-to-losses scaling method on the energy consumption considering different power scaling factors and driving cycles, as compared to high-fidelity scaling methods
Desreveaux, Anatole. "Impact de facteurs techniques sur la consommation énergétique de véhicules électriques." Thesis, Lille 1, 2020. http://www.theses.fr/2020LIL1I004.
Global Warning is one of the major challenges for the 21st century. The transport sector is one of the biggest emitters of greenhouse gas. Electric Vehicles (EVs) are one of the solutions able to reduce those emissions. However, the driving range of the vehicle is one of the barriers for EVs’ adoption. The Campus of University with Mobility based on Innovation and carbon Neutral (CUMIN) program aims at reducing the greenhouse gas emissions produced by mobility at campus “Cité Scientifique” of the University of Lille. EVs are one of the solutions studied to reduce emissions on this campus. For this solution, the university wishes to study the implementation of charging stations to promote EVs. In order to do this, a tool for estimating the energy consumption of an EV is required.Many factors have an impact on the energy consumption of EVs or their driving range. It is necessary to evaluate the effects of the different factors so as to have a better estimation of the driving ranges of those cars. In this PhD Thesis, the impact of different factors on the energy consumption of an Electric Vehicle has been assessed with a simulation tool developed on purpose. The suggested tool takes into account the energy consumption of the traction system, the Heating, Ventilation and Air Conditioning (HVAC) system and the other auxiliaries of the vehicle. This tool has been developed with Energetic Macroscopic Representation. This formalism aims at organizing the model using a forward approach. With this approach, it is possible to take into account the limitations of the system in the simulation tool of the vehicle. In this thesis, the modeling of the different parts have been developed, then validated with experimental tests. Finally, simulations have been carried out to evaluate the impact of the different factors on the energy consumption of an EV
Baouche, Fouad. "Outils pour l'optimisation de la consommation des véhicules électriques." Thesis, Vaulx-en-Velin, Ecole nationale des travaux publics, 2015. http://www.theses.fr/2015ENTP0003/document.
The current ecological and economic context encourages the authorities and the public to reduce CO2 emissions and oil dependence. The transportation is responsible for 23% of pollutants emissions in the world, and this proportion increases up to 37% in France/ The adoption of new transport solutions is primordial to reduce these emissions. Electro mobility is a viable alternative to conventional vehicles. While electric vehicles offer mobility with zero emissions, some of their characteristicds impede their development. The main obtacle to the adoption of these vehicles is the limited autonomy, a sparse distribution of charging stations in urban areas as well as a significant charging time. Also, to promote the use of this type of mobility, it is primordial to develop tools that optimize the energy consumption and take in to account the characteristics associated with this type of mobility. To achieve this, three areas are difined: modeling of electric vehicles, optimized charging station deployment and eco routing. The first part of this theis focuses on the consumption estimation of the electric vehicles and the presentation of the dynamic model library VEHLIB. The second part is dedicated to optimal allocation of charging stations; A methodology for the deployment of electric vehicle charging infrastructures is proposed for the urban area o fthe city of Lyon, taking into account the mobility demand derived from the household travel surveys.The third part of the thesis deals with the eco-routing (green routing). A multi-objective methodology for eco routing with recharge en-route is proposed. The solutions take into account battery state does not permit to finish the trip.Finally, an experiment was carried out using an electric vehicle equipped with position and consumption sensors in order to validate the proposed methodologies and analyze exogenous factor that impact the electric vehicle consumption
Diop, Daour. "Contribution à la gestion de l'énergie d'un véhicule hybride série." Besançon, 2004. http://www.theses.fr/2004BESA2003.
This work presents the energy management of a series hybrid vehicle. It is a platform equipped with three sources of energy, two thermal engines involving each one an alternator-rectifier, and a battery. The objective is to provide energy necessary for the operation of the traction motors and the auxiliaries. The study was undertaken by a hierarchical step. The first chapter models the sources of energy while starting with the battery. The estimate of its state of charge is obtained by parametric identification. Then a look-up table model of the thermal engine is developed. Two alternators - converters are modelled and associated to diesel engines. The chapter 2 treats the optimal sharing of power between the two power generating units of which one is at fixed speed and the other at variable speed. The solved problem is an optimization with like constraint the minimization of the fuel consumption. The results obtained show the interest of the group at variable speed at low power. The last part of the report is devoted to simulation and the implementation in real time of the system. This chapter studies the management of the instructions of injection for the thermal engines and the development of the instructions for control of current through the DC side of the rectifiers. The interconnection of the models of the sources to the signals of the calculator or HEART of the system made it possible to simulate the behaviour of the sources of energy of the vehicle. Finally the diagram of implementation in real time is presented, the models being replaced by the real subsets of the bench. It appears, through this study, the undeniable interest of the series hybrid vehicle to answer the insufficiencies of the electric vehicle limited by its autonomy. The first tests showed the direct impact of the laws of energy management and their performance on the use of series hybrid electric vehicle
El, Khoury Georges. "Etude et simulation de systèmes de climatisation adaptés aux véhicules hybrides." Paris, ENMP, 2005. http://www.theses.fr/2005ENMP1357.
This dissertation aims at analyzing the impact of the air-conditioning system on hybrid vehicles by using data of the additional fuel consumption due to MAC operation. Those data are obtained on roll benches (UTAC and CRF) and test benches (CEP and VALEO) dedicated to mobile air conditioning systems. Tests on Prius I show that energy savigs due to hybridization are compromised when the air conditioning system is driven by a mechanical compressor, which requires operation of the engine when the vehicle is stopped. Electrical and hybrid compressors have been tested. Air conditioning loops integrating those compressors are simulated via a set of MACLIB routines developed during this thesis in Matlab/Simulink language. MACLIB is then integrated in the ADVISOR simulator in order to evaluate additional fuel consumptions of the different air conditioning systems installed on a reference hybrid vehicle. Some simulations have been validated by tests performed on roll benches at UTAC, on the Prius II equipped with an electric compressor. Once MACLIB has been validated, comparative analyses of air conditioning systems either mechanical, or electrical, or hybrid (mechanical/electrical) installed on the reference vehicle, have been performed. Those analyses end by the evaluation of the annual additional fuel consumption of mobile air conditioning systems operating under two European climatic conditions
Trigui, Rochdi. "Motorisation asynchrone pour véhicules électriques : modélisation, optimisation et évaluation." Vandoeuvre-les-Nancy, INPL, 1997. http://www.theses.fr/1997INPL064N.
Nguyen, Bao Huy. "Stratégies de gestion d’énergie pour véhicules électriques et hybride avec systèmes hybride de stockage d’énergie." Thesis, Lille 1, 2019. http://www.theses.fr/2019LIL1I045/document.
Electric and hybrid vehicles are among the keys to solve the problems of global warming and exhausted fossil fuel resources in transportation sector. Due to the limits of energy sources and energy converters in terms of power and energy, hybridizations are of interest for future electrified vehicles. Two typical hybridizations are studied in this thesis: • hybrid energy storage subsystem combining batteries and supercapacitors (SCs); and• hybrid traction subsystem combining internal combustion engine and electric drive. Such combined energy sources and converters must be handled by energy management strategies (EMSs). In which, optimization-based methods are of interest due to their high performance. Nonetheless, these methods are often complicated and computation consuming which can be difficult to be realized in real-world applications.The objective of this thesis is to develop simple but effective real-time optimization-based EMSs for an electric car and a parallel hybrid truck supplied by batteries and SCs. The complexities of the studied system are tackled by using Energetic Macroscopic Representation (EMR) which helps to conduct reduced models for energy management at the supervisory level. Optimal control theory is then applied to these reduced models to accomplish real-time EMSs. These strategies are simple due to the suitable model reductions but systematic and high-performance due to the optimization-based methods. The performances of the proposed strategies are verified via simulations by comparing with off-line optimal benchmark deduced by dynamic programming. Moreover, real-time capabilities of these novel EMSs are validated via experiments by using reduced-scale power hardware-in-the-loop simulation. The results confirm the advantages of the proposed strategies developed by the unified approach in the thesis
Dahbi, Mohamed. "Contribution à l'amélioration des performances des actionneurs dans un véhicule électrique." Electronic Thesis or Diss., Amiens, 2020. http://www.theses.fr/2020AMIE0007.
This thesis concerns the improvement of brushless DC motor performance, called Brushless motor (BLDC), and of an electric vehicle using this type of motor (BLDC) for its propulsion. The aim of this thesis is to provide new methods dedicated to the reduction of problems concerning this type of engine and thus increase its efficiency to achieve a lower electric vehicle energy consumption. This is done while taking into account the different parameters that come into consideration when rolling a vehicle, namely the resistive forces such as aerodynamic forces, rolling, slope, and acceleration. An experimental platform was thus implemented and on which the elaborated methods were implemented and proved after the analysis of the analytical and simulation results. These were developed on the MATLAB / Simulink environment. The proposed methods deal with problems related to current ripple, current peaks, and also the appropriate control mode for increased efficiency
Boucharel, Paul. "Conception des lois de commande optimales pour l'amélioration de l'efficacité globale d'une chaîne de traction automobile." Toulouse, INPT, 2003. http://www.theses.fr/2003INPT060H.
The main aim of the study is to determine the minimal fuel consumption of a parallel hybrid vehicle that fulfill the driver's request. First, a model representing the energy flows inside the vehicle was set. Then local control algorithms were developed to determine the optimal gear ratio and torque repartition between the motors by minimizing a criterion including consumption and driveability aspects. A second point of the thesis consists in extracting the optimal behavior of the car on a planned trip. A global optimization that computes the minimal consumption on the planned trip was developed. Considering a vehicle with a navigation system, the analysis of the results allows to improve the gear ratio and the battery charging management of the local algorithms. Fast prototyping tests and vehicle tests were made to validate this approach
Bouallaga, Anouar. "Gestion énergétique d’une infrastructure de charge intelligente de véhicules électriques dans un réseau de distribution intégrant des énergies renouvelables." Thesis, Lille 1, 2015. http://www.theses.fr/2015LIL10043/document.
Energy and environmental crisis have prompted the government to take strong measures to stimulate energy transition and accelerate green growth. In this context, electric vehicles (EVs) are considered as a real solution to deal with the current problems. Their integration into the electrical system promotes distribution system operators to develop smart solutions in this field. Concerning the Smart Grids concept, the present work aims to provide answers to a wide range of questions for demand side management program using plug-in EVs charging strategies. The first section of this PhD project, presents a methodology to assess technical and economic impacts of EVs charging on Medium and Low voltage distribution networks. Afterwards, analyses about the competitive EVs load management ancillary services are conducted in the third chapter. By comparing potential and opportunities of each ones, three ancillary services for electricity market contribution were selected. In this context, a methodology for designing energy management strategies is proposed. The latter is applied to the selected ancillary services to assess the financial contribution of the developed strategies. Environmental aspects and Wind-to-Vehicle concept are also evaluated. Furthermore, thanks to a co-simulation interface, the interactions between supervision strategies and real distribution networks are analyzed. The last section presents a Hardware-in-the-loop demonstrator using a real time simulator, smart meters and EVs charging stations. Through experiments, communication constraints and Smart Grids principles are evaluated and validated
Miro, Padovani Thomas. "Loi de gestion d'énergie embarquée pour véhicules hybrides : approche multi-objectif et modulaire." Thesis, Orléans, 2015. http://www.theses.fr/2015ORLE2047/document.
The hybrid electric vehicle uses two different energy sources to propel itself: fuel as well as a reversible electric storage system. The energy management strategy aims at supervising the power flows inside the powertrain by choosing the operating points of the different components so as to optimize a given criterion. The energy management strategy is formulated as an optimal control problem where the criterion to be minimized takes into account the total fuel consumption of the vehicle on the considered trip. The optimal solution can be calculated off-line when the vehicle’s mission is perfectly known, an assumption no longer admissible for an embedded strategy whose main objective is to get as close as possible to the optimal result. The work presented in this manuscript highlights the potential of multi-objective optimal control to handle the features’ trade-offs inherent to the development of production vehicle. An energy management strategy taking into account the trade-off between fuel consumption and drivability, as well as one dealing with the trade-off between fuel consumption and battery state of health, are proposed. The presented strategies share a modular approach following the transversal solution of the Equivalent Consumption Minimization Strategy (ECMS). As a result, the control policy of the plug-in hybrid electric vehicle, the Mild-Hybrid, together with complex hybrid architectures provided with an automated transmission, two electric machines or two electric storage systems, is tackled through a common base. This approach allows to reduce the development period of the energy management strategies which shares a maximum of common elements
Mehar, Sara. "The vehicle as a source and consumer of information : collection, dissemination and data processing for sustainable mobility." Thesis, Dijon, 2014. http://www.theses.fr/2014DIJOS069/document.
Today, vehicles have become more sophisticated, intelligent and connected. Indeed, they are equipped with sensors, radars, GPS, communication interfaces and high processing and storage capacities. They can collect, process and communicate information related to their working conditions and their environment forming a vehicular network. The incorporation of communication technologies on vehicles garnered a huge attention of industry, government authorities and standardizations organizations and opened the way for innovative applications that revolutionized the automotive market with the main goals to ensure safety on roads, increase transport efficiency and provide comfort to drivers and passengers. In addition, transportation is still an actively evolving sector. More sustainable means of transportation such as electric vehicles are introduced progressively to the automotive market with new challenges related to energy consumption and environment preservation that remain to be solved. Many research investigations and industrial projects are done to exploit the advantages of information and communication technologies (ICT) to fit with transportation challenges. However, having connected and cooperative vehicles creates a highly dynamic network characterized by frequent link breaks and message losses. To cope with these communication limitations, this thesis focuses on two major axis: (i) connected vehicle or connected mobility and (ii) sustainable mobility. In the first part of this thesis, data dissemination, collection and routing in vehicular networks are addressed. Thus, a new dissemination protocol is proposed to deal with frequent network fragmentation and intermittent connectivity in these networks. Then, a new deployment strategy of new communication infrastructure is developed in order to increase network connectivity and enhance the utilization of the network resources. Finally, a new routing protocol, for delay-sensitive applications, that uses the optimized infrastructure deployment is proposed. The second part focuses on sustainable mobility with a focus on electric vehicles and with the main objective is to reduce pollution issues and make better use of energy. A new architecture for electric vehicles fleet management is proposed. This latter uses the implemented protocols of the first part of this thesis in order to collect, process and disseminate data. It helps to overcome the limitations related to short autonomy of electric vehicles. Then, to meet energy balance challenges, a new deployment scheme for electric vehicles charging stations is developed. This solution helps to satisfy drivers’ demands in term of energy while taking into account available resources
Michel, Pierre. "Gestion d'énergie d’un véhicule hybride électrique-essence équipé d'un catalyseur par minimisation conjointe consommation-pollution : étude et validation expérimentale." Thesis, Orléans, 2015. http://www.theses.fr/2015ORLE2006.
In hybrid gasoline-electric vehicles, the energy management strategies determine the distribution of engine and motor energy flows with fuel consumption reduction as classical objective. Furthermore, to comply with pollutant emissions standards, SI engines are equipped with 3-Way Catalytic Converters (3WCC) heated by exhaust gases. When 3WCC temperature is over the light-off temperature, engine pollutant emissions are almost totally converted. Most of the pollution is produced at the vehicle start, when the 3WCC is cold and the engine pollution is not converted. The 3WCC heating is thus the key aspect of the pollutant emissions. This dissertation proposes an approach to take into account pollutant emissions in energy management. The hybrid electric vehicle is considered as a dynamic system with two states, the battery state of charge and 3WCC temperature. A dynamic optimization problem is defined, minimizing an original criterion weighting judiciously fuel consumption and pollutant emissions. Optimal control theory, with the Pontryaguine Minimum and Bellman principles, allows solving this optimization problem. Optimal strategies are derived and simulated with a vehicle model including a multi-zones 3WCC thermal model, experimentally validated, which simulates precisely the 3WCC heating. The compromise between fuel consumption and pollutant emissions is explored. Then, an innovative 3WCC heating strategy is proposed and validated experimentally in a HyHIL (Hybrid Hardware In the loop) environment. A significant reduction of the pollutant emissions is obtained, strengthening the dynamic optimal approach to set up the energy management strategies for hybrid vehicles
Gouin, Victor. "Évaluation de l’impact du Smart Grid sur les pratiques de planification en cas d’insertion de production décentralisée et de charges flexibles." Thesis, Université Grenoble Alpes (ComUE), 2015. http://www.theses.fr/2015GREAT097/document.
The Smart Grids are the combination of electrical networks and new information and communication technologies. They deal with a change of paradigms that are the insertion of distributed generation and the development of new forms of consumption, such as electric vehicles and prosumers. These changes induce many constraints on networks both aging and historically not sized for this context. This thesis studies the impact of these paradigms on the rules for electrical distribution networks planning. A first tool using an adapted simulated annealing algorithm and methods from graph theory was developed to size the networks at low cost, according to the usual rules for planning. Secondly, a methodology combining a Monte Carlo approach and the construction of annual load profiles was proposed to analyze the impact of distributed generation and electric vehicles in an environment subject to uncertainties. The third stage of the work was to implement advanced distribution automations as an alternative to reinforcement, which is very expensive. This part is focused on demand side management. Finally, a new operational planning combining the previous developed tools was created to move towards the planning of the Smart Grids
Basma, Hussein. "Energy management strategies for battery electric bus fleet." Thesis, Université Paris sciences et lettres, 2020. http://thesesprivees.mines-paristech.fr/2020/2020UPSLM036_archivage.pdf.
Initiatives to decrease emissions from the transport sector are increasing worldwide by seeking alternative technologies to replace oil-based mobility. Battery Electric Buses (BEB) present a promising solution thanks to their high energy efficiency, low greenhouse gas emissions and the absence of local pollutant emissions. However, this technology still faces many challenges, especially its high total cost of ownership (TCO) and other operational factors such as the limited bus driving range, the high energy refueling time, and the required charging technologies and strategies. In this context, this thesis presents a systematic methodology that aims at developing solutions to help overcoming these challenges by providing optimal battery sizing and charging strategy for BEB. First, a comprehensive multi-physical bus energy model is developed to evaluate its energy needs considering all the energy systems encountered within. The energy consumption of the bus is then evaluated at a variety of operating conditions. Then, a techno-economic model of an entire bus line is developed in order to assess the impact of different battery sizing and charging strategies on the costs and operation of BEB. A TCO model is introduced considering the BEB unit costs, battery purchase and replacement costs, energy and power costs, infrastructure, and maintenance costs. A case study in Paris city is presented and the analysis reveals the resulting tradeoff between the TCO and BEB schedule disruptions and delays as function of different battery sizes and charging strategies. A methodology to minimize the TCO of BEB deployment is presented providing the optimal battery sizing and charging strategy for BEB, while respecting the BEB operation constraints. The methodology is a 2-step optimization algorithm that utilizes both Dynamic programming and Genetic Algorithm optimization routines. The results show that the proposed methodology could reduce the BEB TCO between 15-25% compared to the currently adopted approaches to deploy BEB
Carlos, Da Silva Daniel. "Development of a closed-form modeling methodology for the subsystems of electric vehicles : optimization of energy performance." Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPAST014.
To maximize the contribution of hybrid electric vehicles (HEV) to the decarbonization of the transportation sector, it is essential to maximize their energy performance during the design phase. However, the additional power pathways to propel the vehicle act both as an advantage and an added layer of complexity. Indeed, evaluating the consumption of an HEV requires defining a supervisory control, known as Energy Management Strategy (EMS). Therefore, optimizing the design entails combining a static optimization problem (system's plant) with a time-dependent problem (its control), both of which must be considered in tandem.This plant/control co-optimization is typically tackled through either nesting optimal control algorithms within each iteration of a general optimization algorithm for the plant, or employing convex optimization to simultaneously optimize both layers. However, the former approach is known to be limited by computational constraints, while the latter may impact modeling fidelity due to convexity constraints.As a different perspective, this thesis introduces a methodology for developing explicit models to estimate powertrain energy consumption, referred to in this work as the Explicit Powertrain Consumption Model (EPCM). They are developed using component models to account for power losses, then by introducing a second modeling level to consider the impact of sizing variations on loss estimation. Such a formulation can be used as a computationally efficient objective function of an optimization problem that remains static, while enabling human-explainable analysis for reduced problems.The thesis presents the methodology development while using a Fuel Cell Hybrid Electric Vehicle (FCHEV) as a reference vehicle. Besides modeling components commonly found in electric vehicles, it includes a model for the fuel cell system, while further considering models for the power electronics, often overlooked in vehicle design studies. It first introduces the considered component models, then the models for the sizing variation (i.e., the predictive models), before developing the EPCMs and using them for the co-optimization.The validation of the component models using a Toyota Mirai~II on a roller test bench presents an overall error of less than five percent, while the study to assess the impact of the predictive models on the hydrogen consumption resulted in errors below two percent when compared to reference models. Then, an assessment of the usage of EPCMs explores the assumptions required to ensure an explicit formulation; and the co-optimization of the Mirai~II powertrain shows that an EPCM using an affine EMS can be a fair approximation for the co-optimization at the vehicle's first design stages, while reducing the evaluation time by a factor of 100. This study is further extended with reduced problems to observe the impact of the EM sizing only, then of the hybridization level, resulting in linear and quadratic expressions for the fuel consumption and the optimization constraints, which can be used to quickly derive analyses of the vehicle's energy performance.Although the results show that the current state of the methodology can be used for the co-optimization of FCHEVs, the thesis further explores its improvement points and suggests alternative applications to solidify its validity and relevance
Vu, Ngoc Tuan. "Dynamique régénérative du véhicule : Transfert de puissance optimal par la maîtrise des comportements du véhicule de distribution." Thesis, Lyon, INSA, 2014. http://www.theses.fr/2014ISAL0104/document.
In this work, we have studied the energy optimal transfer by controlling the delivery vehicle behaviors. We studied, in particular, the energy consumed by a hybrid vehicle in the urban area. This context led us to investigate the use of a regenerative dynamics by taking into account the vehicle lateral dynamics on a variety of architectures associated with a method for controlling an over-actuated system. To do this, we have developed: (i) a modular virtual test bench to study the energy terms of delivery hybrid vehicle, (ii) an optimal control to determine the actuator inputs of over-actuated system, (iii) and regenerative dynamics to manage energy by taking into account the vehicle lateral dynamics. The virtual test bench constructed in this work allow for studies of the energy consumed for all architectures without changing of each module. This bench is composed the models of vehicle dynamics, steering, traction, braking, and electrical components systems. All models of this bench have been validated by experiments. It provides us the ability to validate and justify the control inputs of actuators and to evaluate the energy consumed terms. The optimal control module by using the allocation controller was also built in this work. It allows us to determine the optimal inputs of the actuators and to simulate the behaviors of all vehicle architectures under the constraints related with different architectures. The results show that the allocation controller is sufficient to determine the actuator inputs and to ensure the vehicle stability without the integration of additional criteria in the optimization problem. The energy gains in comparison with conventional architecture, which have been determined, ensure that the proposed approach effectively reduce the energy consumed by the vehicle. The parametric studies show that the regenerative dynamics can be used to recover energy in the case where the actuators have a very good performance and fast dynamics. In this case, the principle of regenerative dynamics is being improved for delivery vehicles (heavy load and in urban areas)
Maamria, Djamaleddine. "Méthodes d’optimisation dynamique de systèmes à plusieurs états pour l'efficacité énergétique automobile." Thesis, Paris, ENMP, 2015. http://www.theses.fr/2015ENMP0024/document.
Energy management system (EMS) for hybrid vehicles consists on determining the power split between the different energy sources in order to minimize the overall fuel consumption and/or pollutant emissions of the vehicle. The objective of this thesis is to develop an EMS taking into account the internal temperatures (engine temperature and/or catalyst temperature). In a first part and using a prior knowledge of vehicle driving cycle, the EMS design is formulated as an optimal control problem. Then, the PMP is used to solve this optimization problem. Based on the obtained numerical results, some trade-off between performance of the control strategy and complexity of the model used to calculate this strategy is established. The various problems studied in this thesis are examples of successive model simplifications which can be recast in the concept of regular perturbations in optimal control under input constraints discussed here. In a second part, the feedback law of ECMS is generalized to include thermal dynamics. This defines sub-optimal feedback strategies which we have tested numerically and experimentally