WorldCat Identities

Bouquain, David (1976-....).

Works: 11 works in 12 publications in 2 languages and 13 library holdings
Roles: Opponent, Thesis advisor, Author
Publication Timeline
Most widely held works by David Bouquain
Contribution à la modélisation et à l'optimisation des architectures de véhicules hybrides by David Bouquain( Book )

2 editions published in 2008 in English and held by 3 WorldCat member libraries worldwide

Les véhicules électriques et hybrides sont constitués de différents composants et organes : la (ou les) source d'énergie, son stockage et sa conversion, la (ou les) motorisation, la transmission mécanique et/ou électronique (pour les véhicules complètement électriques), la commande et la gestion des différents composants (outils de commande, cartes électroniques, bus véhiculant la puissance et l'information) ... Chaque organe possède sa propre physique mais également une dynamique appropriée. Il constitue à lui seul un sous système nécessitant ainsi une approche de modélisation et de simulation bien particulière. La première partie présente un état de l'art des solutions électriques et hybrides existantes en prenant comme base le véhicule à combustion interne classique placé dans son contexte environnemental. Les différents moyens de stockage de l'énergie électrique sont exposés et comparés. Un des objectifs était le développement d'un outil de dimensionnement énergétique intégré et modulaire, basé sur des modèles physiques dont la précision est à plusieurs niveaux selon l'usage. Cet outil doit servir à terme à l'optimisation, au dimensionnement et à la conception des architectures hybrides par une approche de prototypage virtuel. La mise en place de bancs d'essais modulaires a permis d'évaluer différentes technologies dans le domaine des motorisations électriques et hybrides. De plus, ces outils ont permis de valider des modèles numériques des composants ainsi que les lois de gestion d'énergie. La dernière partie montre les nombreux résultats de simulations et d'expérimentations obtenus validant ainsi nos méthodes de conception et de modélisation
Integration of Plug-in Hybrid Electric Vehicle using Vehicle-to-home and Home-to-Vehicle Capabilities by Florence Berthold( )

1 edition published in 2014 in English and held by 1 WorldCat member library worldwide

The challenge for the next few years is to reduce CO2 emissions, which are the cause of global climate warming. CO2 emissions are mainly due to thermal engines used in transportation. To decrease this emission, a viable solution lies in using non-polluting electric vehicles recharged by low CO2 emission energy sources. New transportation penetration has effected on energy production. Energy production has already reached peaks. At the same time, load demand has drastically increased. Hence, it has become imperative to increase daily energy production. It is well-known that world energy production is mainly produced thermal pollutant power plants, except in Québec, where energy is produced by hydro power plants.The more recent electricity utility trend is that electric, and plug-in hybrid electric vehicles (EV, PHEV) could allow storage and/or production of energy. EV/PHEV batteries can supply the electric motor of the vehicle, and act as an energy storage that assists the grid to supply household loads. This power flow is called vehicle-to-grid, V2G. In this dissertation, the V2G power flow is specifically called vehicle-to-home, V2H. That is battery is used during peak. Moreover, the EV battery is charged during the night, when energy production is low and cheap. This important aspect of V2H is that the vehicle battery is not connected to the grid, but is a part of a house micro-grid.This dissertation presents an offline optimization technique, which includes different energy flows, between the home, EV/PHEV, and a renewable energy source (such as photovoltaic - PV and/or wind) which forms the micro-grid. This optimization has been realized through the dynamic programming algorithm. The optimization objective is to minimize energy cost, including fuel cost, electricity cost, and renewable energy cost.Two fuzzy logic controllers, one located in the vehicle and the second one in the house, have been designed, tested by simulation (online simulation) and validated by experiments.The research analyses two seasonal case studies: one in winter and the other one in summer. In the winter case, a cost reduction of 40% for the offline simulation, 27% for the online simulation and 29% for the experiment is realized whereas in the summer case a cost reduction of 62% for the offline simulation, 60% for the online simulation and 64% for the experiment is presented
Conception et gestion de l'énergie des architectures pour véhicules hybrides électriques by Alexandre Ravey( )

1 edition published in 2012 in English and held by 1 WorldCat member library worldwide

Hybrid electric vehicle have known a quickly grow in the last 10 years.Between conventional vehicles which are criticized for their CO2 emissionand electric vehicles which have a big issue about autonomy, hybrid electricones seems to be a good trade of. No standard has been set yet, and the architecturesresulting of theses productions vary between brands. Nevertheless,all of them are design as a thermal vehicle with battery added which leadsto bad sizing of the component, specially internal combustion engine andbattery capacity. Consequently, the control strategy applied to its componentshas a lot of constraints and cannot be optimal.This thesis investigate a new methodology to design and control a hybridelectric vehicle. Based on statistical description of driving cycle and the generationof random cycle, a new way of sizing component is presented. Thecontrol associate is then determined and apply for different scenarios : firstlya heavy vehicle : A truck and then a lightweight vehicle. An offline controlbased on the optimization of the power split via a dynamic programmingalgorithm is presented to get the optimal results for a given driving cycle.A real time control strategy is then define with its optimization for a givenpatterns and compared to the offline results. Finally, a new control of plug inhybrid electric vehicle based on destination predictions is presented
Modélisation, dimensionnement et optimisation d'un capteur hybride pour la détection des deux roues motorisées dans le trafic routier by Hamza Kerbouai( )

1 edition published in 2015 in French and held by 1 WorldCat member library worldwide

For several years the road safety numbers show the need to develop a technological tool that aims to know thepowered two wheelers vehicles behavior (2PW) to improve their security. From this problematic arise our researchworks that come under the project METRAMOTO (Powered two wheelers traffic measurement for road safety andrisks assessment). The main objective is modeling, sizing and optimization of an hybrid sensor consisted ofelectromagnetic loops and piezoelectric shock sensors. The idea is to use electromagnetic loops to discriminate the2PW presence from the other vehicles, combined with piezoelectric segments to detect the shocks produced by thevehicles wheels passage, all associated with a management algorithm and data processing. Today the sizing of thedetection systems based on electromagnetic loops or piezoelectric cables is done experimentally on controlled sitesusing several vehicles types. This technique requires significant test series which are costly and dangerous. Thisstudy aims to modeling the different interactions between the studied sensor and vehicles in order to its sizing.Electromagnetic and electromechanical models are developed to describe the different interactions that take placebetween electromagnetic loops on the one hand, between electromagnetic loops and vehicles on the other handand those between vehicle wheels and piezoelectric cable. On the basis of established models, a general approachis elaborated driving to sizing the hybrid sensor for any given road. We are also interested to the data processingcoming from the hybrid sensor for which we propose an approach to identifying the different vehicle categoriesincluding the 2PW. Two sensor configurations for two different roads are then proposed. They are associated atdata processing algorithms allowing the acquisition of loops and cables signals, the distinction between the differentvehicles classes, the estimation of the vehicles positions on the road and the measuring of their speed
Coordination mechanisms for smart homes electric energy management through distributed resource scheduling with demand response programs by Berk Celik( )

1 edition published in 2017 in English and held by 1 WorldCat member library worldwide

Grid modernization through philosophies as the Smart Grid has the potential to help meet the expected world increasing demand and integrate new distributed generation resources at the same time. Using advanced communication and computing capabilities, the Smart Grid offers a new avenue of controlling end-user assets, including small units such as home appliances. However, with such strategies, decisions taken independently can cause undesired effects such as rebound peaks, contingencies, and instabilities in the network. Therefore, the interaction between the energy management actions of multiple smart homes is a challenging issue in the Smart Grid. Under this purpose, in this work, the potential of coordination mechanisms established among residential customers at the neighborhood level is evaluated through three studies. Firstly, coordinative home energy management is presented, with the aim to increase local renewable energy usage in the neighborhood area by establishing energy trading among smart homes, which are compensated by incentives. The control algorithm is realized in both centralized and decentralized manners by deploying a multi-agent system, where neighborhood entities are modeled as agents. Simulations results show that both methods are effective on increasing local renewable energy usage and decreasing the daily electricity bills of customers. However, while the decentralized approach gives results in shorter time, the centralized approach shows a better performance regarding costs. Secondly, two decentralized energy management algorithms are proposed for day-ahead energy management in the neighborhood area. A dynamic pricing model is used, where price is associated to the aggregated consumption and grid time-of-use scheme. The objective of the study is to establish a more advanced coordination mechanism (compared to previous work) with residual renewable energy is shared among smart homes. In this study, the performance of the algorithms is investigated with daily and annual analyses, with and without considering forecasting errors. According to simulations results, both coordinative control models show better performance compared to baseline and selfish (no coordination) control cases, even when considering forecasting errors. Lastly, the impact of photovoltaic systems on a residential aggregator performance (in a centralized approach) is investigated in a neighborhood area. In the proposed model, the aggregator interacts with the spot market and the utility, and proposes a novel pricing scheme to influence customers to control their loads. Simulation results show that when the penetration level of residential photovoltaics (PV) is increased, the aggregator profit decreases due to self-consumption ability with PV in the neighborhood
Développement d'un modèle multi physique multidimensionnel de pile à combustible à membrane échangeuse de proton en temps réel pour système embarqué by Pierre Massonnat( )

1 edition published in 2015 in French and held by 1 WorldCat member library worldwide

The fuel cell is an electric generator which uses an electrochemical effect discovered in 18 century by ChristianSchönbein. This technology has gotten successively periods of development and periods of void in the pastdecades. After the petrol barrel price rising and the people¿s awareness of environmental problem such asgreenhouse effect, the research in fuel cell field has been increasing constantly. Its higher efficiency compared tothermal technology to produce electricity, the possibility to use no fossil fuel and no pollution final products make thefuel cell an attractive substitution candidate for energy production. However, its cost, life time, power density andother problems related to the fuel storage do not allow it to replace immediately the actual technology which is elderand benefit about scale economy effect. Thus, the fuel cell technology must be improved to become economicallyviable.One of the ways to do it, is to model the fuel cell in order to reflect, analyze and better understand its behavior with aminimal cost. Unfortunately, the fuel cell is a complex system which combines fluidic, thermic and electrochemicaleffects. In literature, many one dimensional real time models have been developed. But to analyze and predict localphenomena, a 2 dimensional model is needed. However, the general two dimensional models use finite elementcalculation methods that cannot be done in real time due to their complex mathematical calculation. In spirit toovercome this calculation complexity problem, the challenge of this thesis is defined: develop a 2 dimensional modelwho are able to be executed in real time on an ordinary computer or an embedded system.In order to achieve the desired real time performance, the physical, mathematical and computer concepts of realtime 2D fuel cell model are developed, combined and integrated with specific organization methods in a C languageprogram which does not requires an important calculation power or memory to run. All the modeling assumptionsand the modified mathematic methods are implanted following an innovative modeling approach.Finally, a 2D, multiphysique, multidimensional real time fuel cell model is developed and its parameters are adjustedwith a real fuel cell stack from different experiments. The results are then analyzed with a structured observationmethod with conclusions given at last
Solid oxide fuel cell modeling and lifetime prediction for real-time simulations by Rui Ma( )

1 edition published in 2018 in English and held by 1 WorldCat member library worldwide

This thesis first presents a multi-physical modeling of a 2D reversible tubular solid oxide cell. The developed model can represent both a solid oxide electrolysis cell (SOEC) and solid oxide fuel cell (SOFC) operations. By taking into account of the electrochemical, fluidic and thermal physical phenomena, the presented model can accurately describe the multi-physical effects inside a cell for both fuel cell and electrolysis cell operation under entire working range of cell current and temperature. In addition, an iterative solver is proposed which is used to solve the 2D distribution of physical quantities along the tubular cell. The reversible solid oxide cell model is then validated experimentally in both SOEC and SOFC configurations under different species partial pressures, operating temperatures and current densities conditions. Meanwhile, a control-oriented syngas fuel cell model includes both hydrogen and carbon monoxide co-oxidation phenomena are also proposed. The developed syngas model is validated experimentally under different operating conditions regarding different reaction temperatures, species partial pressures and entire working range of current densities. The developed model can be used in embedded applications like real-time simulation, which can help to design and test the control and online diagnostic strategy for fuel cell power generation system in the industrial applications.Real-time simulation is important for the fuel cell online diagnostics and hardware-in-the-loop (HIL) tests before industrial applications. However, it is hard to implement real-time multi-dimensional, multi-physical fuel cell models due to the model numerical stiffness issues. Thus, the numerical stiffness of the tubular solid oxide fuel cell (SOFC) real-time model is analyzed to identify the perturbation ranges related to the fuel cell electrochemical, fluidic and thermal domains. Some of the commonly used ordinary differential equation (ODE) solvers are then tested for the real-time simulation purpose. At last, the novel stiff ODE solver is proposed to improve the stability and reduce the multi-dimensional real-time fuel cell model execution time. To verify the proposed model and the ODE solver, real-time simulation experiments are carried out in a common embedded real-time platform. The experimental results show that the execution speed satisfies the requirement of real-time simulation. The solver stability under strong stiffness and the high model accuracy are also validated.Fuel cell are vulnerable to the impurities of hydrogen and operating conditions, which could cause the degradation of output performance over time during operation. Thus, the prediction of the performance degradation draws attention lately and is critical for the reliability of the fuel cell system. Thus, an innovative degradation prediction method using Grid Long Short-Term Memory (G-LSTM) recurrent neutral network (RNN) is proposed. LSTM can effectively avoid the gradient exploding and vanishing problem compared with conventional RNN architecture, which makes it suitable for the prediction of long time period. By paralleling and combining the LSTM cells, G-LSTM architecture can further optimize the prediction accuracy of the PEMFC performance degradation. The proposed prediction model is experimentally validated by three different types of PEMFC: 1.2 kW NEXA Ballard fuel cells, 1 kW Proton Motor PM200 fuel cells and 25 kW Proton Motor PM200 fuel cells. The results indicate that the proposed G-LSTM network can predict the fuel cell degradation in a precise way. The proposed G-LSTM deep learning approach can be efficiently applied to predict and optimize the lifetime of fuel cell in transportation applications
Control of an ultrahigh speed centrifugal compressor for the air management of fuel cell systems by Dongdong Zhao( )

1 edition published in 2013 in English and held by 1 WorldCat member library worldwide

Le compresseur d'air alimentant en oxygène la pile est un élément important dans les systèmes pile à combustible. Le compresseur peut consommer jusqu'à 20% de l'électricité produite dans les cas les plus défavorables. Le choix et le dimensionnement du compresseur, ainsi que son système de contrôle associé, sont directement liés à la performance du système global. La taille et le poids du système de compression d'air doivent être réduits pour le rendre plus adapté aux applications automobiles. En outre, le contrôle du système de compression d'air est également une problématique importante car il affecte l'efficacité et la sécurité de fonctionnement de la pile à combustible. Pour éviter une sous-alimentation en oxygène de la pile, le débit massique d'air fourni doit être géré de façon appropriée en fonction de la demande de la charge électrique. Pendant ce temps, la pression ne doit pas montrer de trop grandes variations ou ondulations qui peuvent endommager la membrane de la pile.Un contrôle à découplage proposé récemment dans la littérature, nommé contrôle à découplage de perturbation (DDC), est utilisé pour le système de compression centrifuge. Le DDC traite les interactions internes comme une perturbation, puis les éliminent dans le contrôle. Les performances du DDC sont comparées à un dispositif de commande en mode glissant décentralisé. Grâce à la comparaison de ces deux contrôleurs, les résultats montrent que le DDC proposé est performant tant pour des cas stables que dynamiques. Le compresseur centrifuge est donc utilisable pour les systèmes pile à combustible automobiles. Sur un banc d'essai hardware-in-the-loop (HIL), le contrôleur proposé est validé avec un modèle de pile à combustible de 10 kW avec des demandes de charge variables. En outre, une méthode d'évitement d'instabilité, à savoir un limiteur de référence, est proposé pour empêcher le dépassement de la ligne de pompage du compresseur. Les résultats expérimentaux montrent que, dans tous les cas, la zone d'utilisation du compresseur est bien cantonnée à droite de la ligne de pompage
Modélisation multi-physique des batteries à base lithium et application à l'estimation de l'état de charge by Nicolas Watrin( )

1 edition published in 2013 in French and held by 1 WorldCat member library worldwide

The use of high power and high energy batteries becomes a fixture in the transport of tomorrow. But this technology is new because until then, lithium batteries were used for mobile applications which consume low energy, such as mobile and computers. The arrival of these technologies in vehicles involves a new way of designing vehicles and mobility in general. But in this approach, car makers have many problems. First of all, onboard electrical power is not one of their main trades, then this technology, though mastered is still subject to some fuzzy techniques. The main constraint of lithium batteries is that it is very difficult to know the amount of energy remaining in the cell. For a mobile phone, the impact is low, but for a vehicle the issues are totally different. That to respond to this question that this paper is structured as follows.First chapter introduces the main lines of lithium technology. Firstly it show why we needed this technology in vehicles, and then detail the function of these cells. In the same chapter, different methods for numerical modeling of cells are introduced, and the methods for estimating the state of charge of the cells.In the second chapter, numerical modeling is detailed. This is to understand and model the behavior of a cell, by performing a numerical model to reproduce the equivalent electrical and thermal behavior. In this thesis an equivalent circuit model is proposed, and the protocol for determining the parameters of this model. Chapter finally closes with the generalization of the numerical model and the protocol for lithium batteries modeling, and for different capacities and Lithium-ion and Lithium-polymer cells.The third and final chapter, offers a state estimator based on the numerical model presented in chapter two, and using a Kalman filter. This chapter provides the adaptive filter to estimate the charge state, but also the filter implementation for simulations. After many comparisons in simulation, the chapter ends with the implementation of the filter in a development board to make an estimation of state of charge in real time, thereby improving the management of cells
Analysis of aging mechanisms in Li-ion cells used for traction batteries of electric vehicles and development of appropriate diagnostic concepts for the quick evaluation of the battery condition by Christian Schlasza( )

1 edition published in 2016 in English and held by 1 WorldCat member library worldwide

In this thesis, the aging mechanisms withing Li-ion cells are analyzed on a theoretical level, supported by an FMEA(Failure ode and Effects Analysis). The focus lies on the group of lithium iron phosphate (LFP) cells used fortraction batteries in electric vehicles. Scope of the experimental part of the thesis is the development of a diagnosticconcept for the quick battery state determination. A group of high capacity LFP cells (70Ah) designed for tractionpurposes in electric vehicles is aged artificially and investigated afterwards by impedance measurements in the timeand frequency domain. Electrochemical impedance spectroscopy (EIS) is found to reveal interesting information onthe battery's State-of-Health (SOH).For the interpretation of the measurement results, battery models are employed. Different equivalent circuit models(ECMs) are compared and an appropriate model is chosen, which is used for the SOC (State-of-Charge)determination and extended for the SOH (State-of-Health) determination. An SOH determination concept isdeveloped, which allows the approximation of the cell capacity in less than 30s, if the battery and environmentalconditions, such as the temperature and the cell's SOC, are known
Analysis and diagnosis of faults in the PEMFC for fuel cell electrical vehicles by Ali Mohammadi( )

1 edition published in 2014 in English and held by 1 WorldCat member library worldwide

In recent years, according to the upcoming challenge of pollution, fuel saving, to use on FCEV is increasing. It can be that fuel cell power train divided in the PEMFC, Batteries, DC/DC converters, DC/AC inverters and electrical motors. The Proton Exchange Membrane Fuel cells (PEMFC) have consistently been considered for transportation application. Characteristic features of PEMFC include lower temperature (50 to 100 °C) and solid polymer electrolyte membrane. In this work, experiments have shown that the temperature distributions can significant influence on the performance of the PEMFC. Also analytical studies have indicated improvement of ionic resistivity of the electrolyte membrane, kinetics of electrochemical reaction and gas diffusion electrodes have directly related to temperature. This work evaluated the effectiveness of temperature on a single and stack fuel cell. In addition, a 3D model is developed by effective of temperature on performance on the fuel cell. In this thesis, two PEM fuel cells have been considered to find out the relationship and analyze the behaviors of the cell voltage and temperature distributions under various operating conditions. An experimental study for voltage and temperature has been executed, using one cell, 12 thermocouples and 12 voltage sensors have been installed at different points of the cell. In this work a new model was proposed to improve the lifetime and reliability of the power train and to detect online faults. Besides, current distributions in different points of the cell based on varying operating conditions are calculated by the Newton Raphson method. On the basis of the developed fault sensitive models above, an ANN based fault detection; diagnosis strategy and the related algorithm have been developed. The identified patterns ANN have been used in the supervision and the diagnosis of the PEMFC drivetrain. The ANN advantages of the ability to include a lot of data made possible to classify the faults in terms of their type
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