L’autonomie limitée du véhicule électrique est le premier frein au développement du marché de l’électrique. La charge inductive dynamique répond à ce problème, en offrant de charger son véhicule en roulant. La principale difficulté est de gérer les variations importantes du couplage magnétique lors du déplacement du véhicule, et ce pendant le transfert de puissance. Une précédente thèse dans l’équipe de recherche sur un prototype de 3 kW avait abouti au concept de recopie de tension, qui stabilise la tension en sortie du coupleur malgré la variation de couplage, et facilite notablement la conception du convertisseur DC/DC faisant interface avec la batterie. La thèse présentée ici porte sur l’adaptation du système pour fonctionner de 20 kW à 30 kW. Cette montée en puissance n’est pas évidente, du fait des importantes contraintes électriques sur les bobines du coupleur (1,4 kV sur le système de 3 kW), et du champ rayonné limité par des références normatives. Tout d’abord, nous proposons une nouvelle commande du circuit résonnant, qui permet de modifier le dimensionnement pour aboutir à des contraintes électriques plus faibles tout en conservant la recopie de tension. Ensuite, une forme de bobine en huit est étudiée pour aider à réduire le champ rayonné. Enfin, une démarche de dimensionnement est établie pour la partie électrique du système, ainsi que pour le coupleur magnétique, alliant modèle analytique et simulations à éléments finis et réduisant considérablement les temps de simulations. Les résultats de l’évaluation des performances du système dimensionné pour la haute puissance sont prometteurs. / The limited electric-vehicle distance range is the main reason hindering the development of the electric transportation market. Dynamic inductive charging solves this problem, offering the possibility to charge while driving. The main issue consists in handling wide magnetic coupling variations when the vehicle is moving, while charging. A previous thesis in the research team on a 3-kW prototype led to the concept of voltage copying, which stabilises the coupler output voltage despite the varying coupling, making it easier to design the DC/DC converter linking the coupler to the battery. The hereby thesis deals with adapting this system to transfer from 20 kW to 30 kW. Raising the power is no small matter, due to the high electrical constraints on the coupled coils (1.4 kV on the 3-kW system), and the radiated field, limited by standardised thresholds. Firstly, a new control of the resonating circuit is proposed, allowing to change the system design to get lower electrical constraints and maintaining voltage copying properties. Then, an eight-shape coil was investigated in order to reduce the radiated field. Finally, a design method was conceived for the electrical part of the system, as well as the magnetic coupler, using jointly analytical models and finite element simulations to reduce simulation times. Results of the evaluated performance for such a high-power system are quite promising.

Cette thèse étudie l'interaction technico-économique entre véhicules électriques et réseaux d'électricité. Le développement récent de la mobilité électrique invite en effet à analyser les impacts potentiels de la recharge de ces véhicules sur les réseaux électriques, mais aussi le soutien que ceux-ci pourraient apporter dans les réseaux du futur. Ce travail s'inscrit résolument dans le cadre des réseaux d'électricité intelligents ; la plupart des résultats de cette thèse s'appliquent tout aussi bien à un lave-linge, un chauffe-eau, une télévision tant que l'on leur prête la capacité d'intelligence ! Dès lors que les décisions des consommateurs électriques flexibles interagissent, ce cadre d'étude offre un terrain de jeu propice aux outils de théorie des jeux. Ceux-ci ont un apport direct lorsque le problème considéré a un fondement stratégique, mais leur application permet aussi de proposer des solutions sur des aspects où la théorie des jeux n'est pas forcément attendue : algorithmique, dans l'échange d'information entre acteurs, etc. La description de cet apport est l'objet principal de ce travail de thèse et se décompose en trois parties. En fil rouge, le cas des profils de charge rectangulaires – soutenus par de nombreux arguments pratiques mais souvent délaissés par les chercheurs – est analysé. En premier lieu, des questions algorithmiques se posent pour coordonner la charge de véhicules électriques dans un même périmètre du système électrique. Proposant et étudiant un algorithme de coordination, il est montré comment les propriétés fondamentales de celui-ci - sa convergence, l'efficacité de ses points de convergence – peuvent être déduite d'un jeu auxiliaire sous-jacent. L'analyse de ce jeu est faite en montrant qu'il appartient à la classe des jeux de potentiel, sous des hypothèses physiques et économiques très générales. Sur le plan de l'échange d'information, un modèle est proposé pour réfléchir à la bonne communication entre un opérateur du réseau et un véhicule. Ces deux agents ont intérêt à communiquer pour planifier la charge intelligente du véhicule électrique, mais ont des objectifs distincts. Ce cadre est très proche du Cheap-talk en théorie des jeux, mais aussi de la problématique de la quantification en traitement du signal. Ce travail tisse au passage des liens entre ces sujets. Il propose aussi une méthode pour que l'agent du réseau et le véhicule s'accordent hors-ligne sur un bon mécanisme d'échange d'information. Enfin, la théorie des jeux est appliquée dans un cadre plus habituel, pour analyser le jeu des acteurs. Ceci est fait quand des ensembles de véhicules de taille importante, vus comme des flottes, cohabitent avec des véhicules individuels. Ceci offre un terrain de jeu applicatif aux outils très récents des jeux composites. Dans ces trois directions de recherche, des simulations sont effectuées dans le cadre d'un réseau de distribution d'électricité, maille du système électrique qui pourrait vivre des impacts significatifs si la charge est non-coordonnée. En particulier, elles montrent la robustesse des méthodes proposées face aux incertitudes sur les données lorsque des profils de charge rectangulaires sont considérés. / This thesis studies the technical and economical interaction between electric vehicles and electrical networks. The recent development of electric mobility leads to the analysis of potential impacts of electric vehicle charging on the electrical networks, but also to the possible support that these particular electric consumers could provide in the future smart grids. In this direction, most of the results given in this thesis also apply to a washing machine, a water-heater, a TV, as soon as these equipments are capable of being smart! When the decisions of flexible electric consumers interact, the considered framework naturally offers a unique exercise area for the tools of game-theory. The interpretation is straightforward when the considered problem is strategic by definition, but these tools allow also shedding light on other aspects: algorithmic coordination, information exchange, etc. The description of the benefits of using game-theory in this context is the aim of this work. This is done according to three aspects. In these three directions, a particular attention is drawn to the case of rectangular charging profiles, which are very practical, but often ignored by the literature. First, algorithmic issues arise when coordinating the charging of electric vehicles in a same area of the electrical network. A charging algorithm is proposed and analyzed. This is done by studying an underlying auxiliary game. This game is proved to belong to the class of potential games under very general physical and economic assumptions. In turn, it inherits from the strong properties of this class of games, namely convergence and an efficiency result in the case of a large number of electric vehicles. Considering information exchange, a model is proposed to design a good communication scheme between an operator of the electrical system and an electric vehicle. Both agents have an interest in exchanging information to schedule optimally the charging profile of the electric vehicle but they do not share the same objective. This framework is closely related to Cheap-talk in game theory and to quantization in signal processing. Amongst others, this work explains interesting connections between both topics. Furthermore, a method, which is used offline, is given to obtain a good communication mechanism between both agents. Finally, game theory is used in its traditional form, studying the strategic interaction when groups of a large number of electric vehicles – seen as fleets – coexist with individual vehicles. This allows the application of the very recent concept of composite games. In the three parts of the work, simulations are conducted in a French realistic distribution network, which could be the first part of the electrical system severely impacted by a non-coordinated charging. This highlights the robustness of rectangular charging profiles against forecasting errors on the parameters of the models.

Aus der Einleitung: "Durch die Verwendung von Kraft-Wärme-Kopplung (KWK) kann sowohl die erzeugte elektrische als auch die anfallende thermische Energie genutzt und somit der Nutzungsgrad der eingesetzten Primärenergie deutlich gesteigert werden. Dieses Konzept wird sowohl in Blockheizkraftwerken (BHKW) wie auch in Range Extendern (RE) verwendet (Ferrari et al. 2012). Die bisher geringe Reichweite von Elektrofahrzeugen wird durch die zusätzlich vom RE bereitgestellte elektrische Energie erweitert. ..."

The new generation of cars are so-called Plug-in Hybrid Electric Vehicles (PHEVs) which has the grid connection capability. By the introduction of these vehicles, the grid issues will be connected to the private car transportation sector for the first time. The cars from the gird perspective can be considered as a regular load with certain power factor. The effects of this type of new load in distribution grid are studied in this thesis. By modelling the cars as regular load, the effects of the cars in three distinct areas in Stockholm are investigated. The car number in each area is estimated based on the population and commercial density of electricity consumption in the three areas. Afterward, the average electricity consumption by the cars in one day is distributed among 24 hours of the day with peak load in the studied year. This distribution is done by two regulated and unregulated methods. The regulated method is based on the desired pattern of electricity consumption of PHEVs by vehicle owners. On the other hand, the regulated pattern is designed based on encouragement of the car owners to consume electricity for charging their car batteries at low-power hours of day (usually midnight hours). The power system from high voltage lines in Sweden down to 11 kV substations in Stockholm simulated in PSS/E software has been used in this study. The automation program (written in Python) is run in order to get the output report (voltage variation and losses) of the load flow calculations for different hours of day by adding the required power for PHEVs both by regulated and unregulated patterns. The results show the possibility of introducing growing number of cars till year 2050 in each area with existing grid infrastructures. Moreover, the number of cars, yearly and daily electric consumption for PHEVs in pure electric mode are shown in this project and the effects of regulated electricity consumption are investigated. It is concluded that since the car number is estimated based on the population, the areas with higher residential characteristics are more problematic for integration of PHEVs from capacity point of view. Moreover, by regulating the charging pattern of PHEVs, the higher number of PHEVs can be integrated to the grid with the existing infrastructures. In addition, the losses have been decreased in regulated pattern in comparison with unregulated pattern with the same power consumption. The voltage in different substations is within the standard boundaries by adding 100 percent of PHEVs load for both regulated and unregulated patterns in all three areas.

Electric vehicle adoption is one of the most prominent discussions currently facing the automotive industry, as this is an inevitable change towards a more sustainable future of transportation. Traditionally, car manufacturers adapt to consumer needs changing, thus prompting high relevance for understanding the consumer perspective and purchasing influences. This study aims to build a deeper understanding of the importance of internal and external factors on the EV consumer decision-making process, as well as to explore how the perception of such factors change upon adoption of electric vehicles. The study follows a positivism approach by conducting deductive research. A conceptual framework is developed based on review of research literature of rational choice theory, the consumer decision-making model, and factors impacting EV consumers, and constructing a model from the findings. Quantitative survey data is then collected following the model presented, and results are obtained using SPSS. Finally, the analysis applies the social identity theory, innovation diffusion theory, and theory of planned behavior for further evaluative discussions. The findings show that internal factors such as environmental awareness and fears and anxieties have a vital impact on consumers’ decisions of EV adoption and evaluation of EV alternatives, while social influences have a relatively small impact on the decision. The findings suggest a link between the theory of planned behavior and changing perceptions upon adoption of EV, in which factors relating to attitudes and perceived behavioral control are more susceptible to changing, while factors relating to subjective norms are not.

Carbon emissions are one of the primary drivers of climate change and the transport sector accounts for 24% of the global carbon emissions. A shift within the automobile industry towards more eco-friendly modes of transportation is hence needed. Vehicles powered by hydrogen are a carbon emissions-free mode of transportation and have been identified as a viable approach to de-carbonize the transport sector, yet, the number of hydrogen-powered vehicles on the roads in Sweden as of 2022 is relatively low compared to the rest of the world. The aim of this study was both to identify factors that are important for actors to invest in hydrogen technology within the transport sector, and to identify how the collaboration between different actors was formed during the adoption process. The study uses a multiple-case study research design where the five cases of Storuman, Mariestad, Sandviken, Trelleborg and Ljungby were selected. Data was collected through eleven semi-structured interviews over video calls. The study has examined the diffusion process of hydrogen technology within the transport sector of each case according to the diffusion of innovations theory. An analysis of the diffusion of hydrogen technology has not, to the best of my knowledge, been conducted in the examined cases. Gaining an understanding of these processes can provide guidance for other municipalities or actors who aims to reduce their emissions and can play an important role in achieving Sweden´s objective of becoming the world´s first fossil-free welfare nation. The findings of the study were that investments in hydrogen technology within the transport sector are currently not economically profitable. However, investments in the innovation were still motivated in terms of a relative environmental advantage, reception of financial funding, the will to take a leading role in the energy transition, geographical location, long-term economic benefits and indirect economic benefits which mainly include that the municipality can market themselves as green and progressive in order to attract competent workforce and business opportunities. The study also concluded that local political support is an important pre-condition for a successful adoption of the innovation.

In diesem Beitrag wird eine Betriebsstrategie für einen hybriden Energiespeicher vorgestellt, die sich der Vorhersage zukünftiger Fahrzustände durch ein autonomes Fahrzeug bedient. Dies ermöglicht ein zusätzliches Verringern der Verluste im Vergleich zu herkömmlichen Strategien, die keine Vorhersagen verwenden. Um diese Funktionen umzusetzen, wurden drei Hierarchieebenen definiert. Die oberste enthält die Energiestrategie und bestimmt den langfristigen Ladestandverlauf des Kondensators mit Hilfe der Vorhersagen. Sie gibt der Leistungsstrategie in der mittleren Ebene einen Sollladestand und eine Zielzeit vor, zu der dieser Ladestand erreicht werden soll. Die Leistungsstrategie ist als modellprädiktive Regelung ausgeführt, die den Zielladegrad in einem Toleranzband führt und die Verluste des Energiespeichersystems minimiert. Die unterste Hierarchieebene enthält die Leistungsregelung des verwendeten DC/DC-Wandlers. Diese stellt die Kondensatorleistung nach der Vorgabe durch die Leistungsstrategie ein. Mit Hilfe dieses Ansatzes und einer Vorausschau von maximal 12 s konnten die Verluste im Vergleich zu einer regelbasierten Strategie ohne Vorausschau um 12 % verringert werden. Im Vergleich zu einer global optimierten Lösung, die mittels einer Dynamischen Programmierung erreicht wurde, erzeugt sie 8 % mehr Verluste. / This paper presents an operating strategy for a hybrid energy storage system using the prediction of future driving conditions by an autonomous vehicle. This allows to reduce the losses compared to conventional strategies that do not use predictions. To implement these functions, three hierarchy levels have been defined. The top level is the energy strategy and determines the long-term state of charge of the capacitor using the predictions. It gives the power strategy, the middle level, a target charge level and a target time at which this state of charge should be reached. The power strategy determines the current power distribution using a model predictive approach and stationary loss optimization. The lowest hierarchical level is the power control of the DC/DC converter used. This adjusts the capacitor power according to the specification of the power strategy. With the help of this approach and a forecast of maximum 12 s, the losses could be reduced by12 % compared to a rule-based strategy without a forecast. In comparison to a globally optimized solution achieved by dynamic programming, the new strategy generates 8 % more losses.

Increase in the awareness environmental conservation is leading the automotive industry into the adaptation of alternatively fueled vehicles. Electric, Fuel-Cell as well as Hybrid-Electric vehicles focus on this research area with aim to efficiently utilize vehicle powertrain as the first step. Energy and Power Management System control strategies play vital role in improving efficiency of any hybrid propulsion system. However, these control strategies are sensitive to the dynamics of the powertrain components used in the given system. A kinematic mathematical model for Plug-in Hybrid Electric Vehicle (PHEV) has been developed in this study and is further optimized by determining optimal power management strategy for minimal fuel consumption as well as NOx emissions while executing a set drive cycle. A multi-objective optimization using weighted sum formulation is needed in order to observe the trade-off between the optimized objectives. Particle Swarm Optimization (PSO) algorithm has been used in this research, to determine the trade-off curve between fuel and NOx. In performing these optimizations, the control signal consisting of engine speed and reference battery SOC trajectory for a 2-hour cycle is used as the controllable decision parameter input directly from the optimizer. Each element of the control signal was split into 50 distinct points representing the full 2 hours, giving slightly less than 2.5 minutes per point, noting that the values used in the model are interpolated between the points for each time step. With the control signal consisting of 2 distinct signals, speed and SOC trajectory, as 50 element time variant signals, a multidimensional problem was formulated for the optimizer. Novel approaches to balance the optimizer exploration and convergence, as well as seeding techniques are suggested to solve the optimal control problem. The optimization of each involved individual runs at 5 different weight levels with the resulting cost populations being compiled together to visually represent with the help of Pareto front development. The obtained results of simulations and optimization are presented involving performances of individual components of the PHEV powertrain as well as the optimized PMS strategy to follow for given drive cycle. Observations of the trade-off is discussed in the case of Multi-Objective Optimizations.

The effects of businesses all over the globe on social issues like climate change have caused an increasing demand for those businesses to take responsibility for their actions. While corporate social responsibility has been concerned with such topics for a while, the more recent concept of ‘creating shared value’ aims to have a more justified approach in a way that it provides economic value for the implementing company while also targeting social issues simultaneously. Still, specific tools helping companies to implement initiatives that create shared value are missing.Multinational large-fleet operators, such as logistics companies or car rental services, are considered to contribute a significant share to the earlier mentioned social issue of climate change. With the rising adoption of electric vehicles by such large-fleet operators, the concept of Vehicle-to-Grid is identified as a way for multinational large-fleet operators to create shared value. Vehicle-to-Grid is a technology that promises to help increase the utilisation of renewable energy sources, thereby helping to tackle climate change. Since the concepts of creating shared value and Vehicle-to-Grid have not been combined so far, a research gap was identified. Therefore, this research aims to answer the questions of how Vehicle-to-Grid can create shared value for multinational large-fleet operators and how expected results of that implementation can be measured for the implementing company, society and other considered stakeholders.Empirical data is collected by qualitatively interviewing organisations that have been involved in Vehicle-to-Grid related projects and is analysed with the help of a conceptual framework that the authors developed. The conclusion of this study closes the identified research gap and contributes to the theory of how shared value initiatives can be implemented. The research suggests that for multinational large-fleet operators, shared value creation by implementing Vehicle-to-Grid could be achieved by redefining productivity in the value chain and enable local cluster development. Additionally, the research gives implications on how progress for all considered parties can be measured and suggests managerial and policy implications that would help to define Vehicle-to-Grid business cases in the future.

Asset managers continue to prepare physical infrastructure investments needed to accommodate the emerging technologies, namely vehicle connectivity, electrification, and automation. The provision of new infrastructure and modification of existing infrastructure is expected to incur a significant amount of capital investment. Secondly, with increasing EV and CAV operations, the revenues typically earned from vehicle registrations and fuel tax are expected to change due to changing demand for vehicle ownership and amount of travel, respectively. This research estimated (i) the changes in highway expenditures in an era of ECAV operations, (ii) the net change in highway revenues that can be expected to arise from ECAV operations, and (iii) the changes in user equity across the highway user groups (vehicle classes). In assessing the changes in highway expenditures, the research developed a model to predict the cost of highway infrastructure stewardship based on current and/ or future system usage. <div><br></div><div>The results of the research reveal that CAVs are expected to significantly change the travel patterns, leading to increased system usage which in turn results in increased wear and tear on highway infrastructure. This, with the need for new infrastructure to support and accommodate the new technologies is expected to result in increased highway expenditure. At the same time, CAVs are expected to have significantly improved fuel economy as compared to their human driven counterparts, leading to a decrease in fuel consumption per vehicle, resulting in reduced fuel revenues. Furthermore, the prominence of EVs is expected to exacerbate this problem. This thesis proposed a revision to the current user fee structure to address these impacts. This revision contains two major parts designed to address the system efficiency and equity in the near and long term. For the near term, this thesis recommended a variable tax scheme under which each vehicle class pays a different fuel tax rate. This ensures that both equity and system efficiency are improved during the transition to ECAV. In the long term, this thesis recommended supplementing the fuel tax with a distance based VMT tax, applicable to electric vehicles.<br></div>