As global climate change concerns, technological advancements, and economic shifts increase the adoption of electric vehicles, it is vital to study how best to integrate these into our existing energy systems. Electric vehicles (EVs) are on track to quickly become a large factor in the energy grid. If left uncoordinated, the charging of EVs will become a burden on the grid by increasing peak demand and overloading transformers. However, with proper charging control strategies, the problems can be mitigated without the need for expensive capital investments. Distributed control methods are a powerful tool to coordinate the charging, but it will be important to assess the trade-offs between performance, information privacy, and computational speed between different control strategies. This work presents a comprehensive comparison between four distributed control algorithms simulating two case studies constrained by dynamic transformer temperature and current limits. The transformer temperature dynamics are inherently nonlinear and this implementation is contrasted with a piece-wise linear convex relaxation. The more commonly distributed control methods of Dual Decomposition and Alternating Direction Method of Multipliers (ADMM) are compared against a relatively new algorithm, Augmented Lagrangian based Alternating Direction Inexact Newton (ALADIN), as well as against a low-information packetized energy management control scheme (PEM). These algorithms are implemented with a receding horizon in two distinct case studies: a local neighborhood scenario with EVs at each network node and a hub scenario where each node represents a collection of EVs. Finally, these simulation results are compared and analyzed to assess the methods’ performance, privacy, and processing metrics for each case study as no algorithm is found to be optimal for all applications.

Dynamically charged vehicles suffer from power-loss during wireless power transfer due to vehicle coil misalignment while driving. Autonomous dynamically charged vehicles can maximize wireless power transfer by following an optimal charging path, but the repeated precision increases road wear. To avoid unnecessary road wear and rutting, a path planner can intentionally inject variability into an autonomous vehicle’s path. However, introducing variability into an optimal charging path risks depleting battery life prior to destination arrival, and it increases rider discomfort. Therefore, a path planner is proposed that guarantees average charging criteria and ensures rider comfort while reducing road wear.

Les supercondensateurs présentent un intérêt grandissant pour des applications embarquées. De récentes études (Supercapacitors USA, 2013) montrent que leur intégration dans un véhicule hybridé électriquement peut contribuer à multiplier par deux la durée de vie des batteries. Cependant, leur vieillissement n’est pas totalement maîtrisé et suscite encore de nombreuses interrogations.L’étude menée dans le cadre de cette thèse aborde la problématique du vieillissement du supercondensateur, et sa mise en application dans une chaîne de propulsion électrique haute tension. Les travaux ont porté sur les modes de vieillissements accéléré par floating (tension et température constantes) et par cyclage (charge décharge à courant constant), et ont permis l’élaboration d’un protocole d’essai fiable et répétitif permettant de minimiser les perturbations lors des mesures en modes fréquentiel et continu dites respectivement AC et DC. Les études faites sur le vieillissement par floating ont permis non seulement d’aboutir à une estimation de la durée de vie des supercondensateurs mais aussi d’analyser certaines causes du vieillissement de ces éléments.Durant cette étude nous avons également intégré un pack de supercondensateurs dans une plateforme d’un véhicule électrique équipé d’un pack de batteries au lithium fer phosphate. Cette étude a permis de mettre expérimentalement en évidence l’apport des supercondensateurs lors de phases transitoires (accélération, freinage, sollicitations brusques) et la réduction induite des sollicitations dynamiques sur la batterie. / Ultracapacitors present a growing interesting in at various the embedded applications. Recently published studies show that different integrations of ultracapacitor in the Hybrid Electric Vehicle (HEV) permits to increase the battery’s lifetime up to twice. In the meantime, the aging of ultracapacitor is not fully known and still waits many questions have to be responded.This thesis is studying the aging of the ultracapacitor and their integration in a HEV. The work focused on the accelerated aging in floating mode such as constant voltage and temperature and also in cycling mode such as charge-discharge for a constant current. This study permits us to find a reliable and a repeatable test protocol in order to minimize the noise during the measurement of a frequencial and a continuous mode. In the meantime, the floating mode allows to estimate the supercapacitors’ lifespan and also to determine some reasons of the aging.Besides, we have also included a pack of ultracapacitors in an EV platform based on a pack of lithium iron phosphate. The experimental test demonstrated clearly a contribution of the ultracapacitors during a transient phase (acceleration, braking, sudden stress) and the dynamic strain reduction on the battery.

<p>Hybrid electric vehicles are considered to be an important part of the future vehicle industry, since they decrease fuel consumption without decreasing the performance compared to a conventional vehicle. They use two or more power sources to propel the vehicle, normally one combustion engine and one electric machine. These power sources can be arranged in different topologies and can cooporate in different ways. In this thesis, dynamic models of parallel and series hybrid powertrains are developed, and different strategies for how to control them are compared.An optimization algorithm for decreasing fuel consumption and utilize the battery storage capacity as much as possible is also developed, implemented and tested.</p>

<p>Hybrid electric vehicles have two power sources - an internal combustion engine and an electric motor. These vehicles are of great interest because they contribute to a decreasing fuel consumption and air pollution and still maintain the performance of a conventional car. Different topologies are described in this thesis and especially the series and parallel hybrid electric vehicle and Toyota Prius have been studied. </p><p>This thesis also depicts modelling of a reference car and a series hybrid electric vehicle in Modelica. When appropriate, models from the Modelica standard library have been used. Models for a manual gearbox, final drive, wheel, chassis, air drag and a driver have been developed for the reference car. </p><p>For the hybrid electric vehicle a continuously variable transmission, battery, an electric motor, fuel cut-off function for the internal combustion engine and a converter that distributes the current between generator, electric motor and internal combustion engine have been designed. </p><p>These models have been put together with models from the Modelica standard library to a reference car and a series hybrid electric vehicle which follows the NEDC driving cycle. A sketch for the parallel hybrid electric vehicle and Toyota Prius have also been made in Modelica. </p><p>Developed models have been introduced into the Modelica library VehProLib, which is a vehicle propulsion library under development by Vehicular Systems, Linköpings universitet.</p>

Performance of two different waste heat recovery systems (one based on Rankine cycle and the other one using thermoelectricity) combined with non-hybrid, mild-hybrid and full hybrid systems are investigated. The vehicle under investigation was a 440hp Scania truck, loaded by 40 tons. Input data included logged data from a long haulage drive test in Sweden.All systems (waste heat recovery as well as hybrid) are implemented and simulated in Matlab/Simulink. Almost all systems are modeled using measured data or performance curves provided by one manufacturer. For Rankine system results from another investigation were used.Regardless of practical issues in implementing systems, reduction in fuel consumption for six different combination of waste heat recovery systems and hybrid systems with different degrees of hybridization are calculated. In general Rankine cycle shows a better performance. However, due to improvements achieved in laboratories, thermoelectricity could also be an option in future.This study focuses on “system” point of view and therefore high precision calculations is not included. However it can be useful in making decisions for further investigations.

The shift to strong hybrid and electrified vehicle architectures engenders controversy and brings about many unanswered questions. It is unclear whether developed markets will have the infrastructure in place to support and successfully implement them. To date, limited effort has been made to comprehend if the energy and transportation solutions that work well for one city or geographic region may extend broadly. A region's capacity to supply a fleet of EVs, or plug-in hybrid vehicles with the required charging infrastructure, does not necessarily make such vehicle architectures an optimal solution. In this study, a mix of technologies ranging from HEV to PHEV and EREV through to Battery Electric Vehicles were analyzed and set in three Canadian Provinces and 3 U.S. Regions for the year 2020. Government agency developed environmental software tools were used to estimate greenhouse gas emissions and energy use. Projected vehicle technology shares were employed to estimate regional environmental implications. Alternative vehicle technologies and fuels are recommended for each region based on local power generation schemes. / UOIT

This thesis takes EV from the late 90’s as a baseline, assess the capability of today’s EV technology, and establishes its near-term and long-term prospects. Simulations are performed to evaluate EVs with different combinations of new electric machines and battery chemistries. Cost assessment is also presented to address the major challenge of EV commercialization. This assessment is based on two popular vehicle classes: subcompact and mid-size. Fuel, electricity and battery costs are taken into consideration for this study. Despite remaining challenges and concerns, this study shows that with production level increases and battery price-drops, full function EVs could dominate the market in the longer term. The modeling shows that from a technical and performance standpoint both range and recharge times already fall into a window of practicality, with few if any compromises relative to conventional vehicles. Electric vehicles are the most sustainable alternative personal transportation technology available to-date. With continuing breakthroughs, minimal change to the power grid, and optimal GHG reductions, emerging electric vehicle performance is unexpectedly high.

The paradigm of personal transportation is changing. Electric vehicles are here. The arrival of the Tesla Roadster, Nissan Leaf, and Chevy Volt has changed the way in which we have to think about the energy that fuels our transportation needs. As PEVs find their way into garages this year and especially in the coming years, the neighborhood, city, state, and regional electric infrastructure will take on a new importance for many people as their interactions with it become significantly more complex and intimate as a result of regular electric vehicle charging.

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