<p>Due to increasing regulation on emissions and shifting consumer preferences, the wide adoption of battery electric vehicles (BEV) hinges on research and development of technologies that can extend system range. This can be accomplished either by increasing the battery size or via more efficient operation of the electrical and thermal systems. This thesis endeavours to accomplish the latter through comparative investigation of BEV integrated thermal management system (ITMS) performance across a range of ambient conditions (-20 °C to 40 °C), cabin setpoints (18 °C to 24 °C), and six different ITMS architectures. A dynamic ITMS modelling framework for a long-range electric vehicle is established with comprehensive sub models for the operation of the drive train, power electronics, battery, vapor compression cycle components, and cabin conditioning. This modelling framework is used to construct a baseline thermal management system, as well as for adaptation to four common systems. Additionally, a novel low-temperature waste heat recovery (LT WHR) system is proposed and shown to have potential benefits at low ambient temperatures through the reduction of the necessary cabin ventilation loading. While this system shows performance improvements, the regular WHR system offers the greatest benefit for long-range BEV drive cycles in terms of system range and transient response. With an optimal thermal management system found for long range BEV’s this system is then used as a boundary condition for a study on cooling of the battery. Battery conditioning, health, and as a result their along cell and system lifetime remains an additional concern of consumers as well as thermal systems engineers seeking to ensure safety and ensure longevity of EV battery cells. Three typical coolant flow orientations are studied to compare them under different flow conditions and thermal interface material performance. The battery cooling model is then coupled to the previously established dynamic modelling environment to demonstrate the added modelling capability (and necessity) for incorporating module-level cooling performance in both battery cooling studies and transient ITMS environments. </p>

Electrical vehicles have become more popular during recent years due to their reduced greenhouse gas emissions. The research within Li-ion batteries is therefore moving fast. Presently, two-level converters transforming the current from DC to AC. However, an alternative method of power conversion is by utilizing modular multilevel converters, which can perform better harmonics than the two-level converter. This study aims to research the impact of these converters on battery cell heat generation. In doing so, developing a digital twin of the Li-ion battery cell, which in this case is a Samsung 28 Ah nickel, manganese, and cobalt prismatic battery cell, focusing on the thermal aspects such as heat generation, heat capacity, and thermal conductivity. The modular multilevel converter may also cause significant overtones, harmonics. Therefore, this study investigates the thermal impact of these frequencies. The results show that it is possible to, via experiments and simulations, determine the heat capacity and thermal conductivity of a Li-ion cell. Furthermore, the frequencies caused by the modular multilevel converter cause a temperature rise in the cell, compared to the two-level converter. Although, if the same root mean square for the modular multilevel converter current is used, the temperature rise is lower compared to DC. During the load cycles, the results show that there are slightly higher temperatures at the positive current collector side compared to the negative. It is, however, the jelly roll core that has the highest temperatures.

The rise of batteries in the industry, especially Li-ion, is increasing rapidly. Li-ion battery systems are traditionally composed of a particular type of cell chemistry fit to the system needs. Due to the significant differences between chemistries, different cells have different attributes. The thesis explores the potential of a heterogeneous solution to include different cells to find a suitable compromise between different attributes. An electrified passenger train using a homogenous solution was evaluated against a heterogeneous solution consisting of two cell types, NMC and LTO, which have significant differences in attributes.  Simulation with models covering the train kinematics, track characteristics, and battery behaviour generates the thesis results. Validation of simulation results includes comparing previous simulations and the new effects of the heterogeneous solution, which indicate a good fit. Verification of the results encompasses a small-scale experiment with a custom-made physical circuit to observe the proposed solution's actual behaviour and verify model validity, which implies the correctness of models and implementation. The results indicate that a heterogeneous solution is possible within the scope of electrified trains. Furthermore, several trade-offs exist between NMC and LTO cells, especially regarding rate capability, safety and capacity, which confirms the potential of heterogeneous battery systems.

Les mutations observées sur le système électrique (production décentralisée, véhicules électriques, stockage, micro réseau...) font émerger des problématiques d'ordres économiques et techniques dans la gestion de ce dernier. Parmi eux, l'impact sur les niveaux de tension et de courant de neutre des réseaux de distribution. Le but de cette thèse est d'étudier des modèles probabilistes pour estimer ces impacts. L'incertitude sur la puissance PV produite et sur l'utilisation des VEs implique la nécessité de développer des modèles probabilistes de consommation et de production d'électricité. Deux modèles différents de production et de consommation ont été étudiés : L'un basé sur l'approximation de données historiques par une densité de probabilité, l'autre reposant sur la répartition des données en groupes définis par un profil type et une probabilité d'occurrence. Des techniques de load flow probabilistes ont été étudiées dans cette thèse pour prendre en compte l'effet intermittente de la production PV et l'incertitude sur la consommation. Une technique basée sur la méthode de simulation Monte Carlo, une deuxième basée sur l'approximation PEM et une dernière basée sur l'utilisation du clustering appelée méthode pseudo Monte Carlo. Après avoir comparé la pertinence des méthodes sur deux réseaux test, la méthode pseudo Monte Carlo est appliquée, pour son gain en temps de simulation et son adaptabilité, dans un cas d'application qui porte sur l'estimation de la probabilité de dépassement des limites du courant de neutre en fonction du déséquilibre de production PV installée. / The current changes on the electrical system bring out economic and technical issues in the management of the latter. Among these issues, the impact of distributed generation and VEs on the technical constraints of the distribution network. The aim of this thesis is to study probabilistic models to estimate the impacts of photovoltaic production and electrical vehicles on medium and low voltage distribution networks. Two different probabilistic models of production and consumption were studied : one based on the fitting of historical data by one probability density function, the other one based on the data clustered in groups defined by a standard profile and a probability of occurrence. Three probabilistic load flow technics have been studied in this thesis. The first is based on the Monte Carlo simulation method, the second is based on the PEM approximation method and the last, based on the use of clustering, is called pseudo Monte Carlo method.