Motivated by the goal of transition to a zero-carbon-emission-based economy for climate change mitigation, electrification opportunities are more promising in the transportation sector. Electric Vehicles (EVs) are at the forefront of the energy transition at an expanded rapid pace in the transportation sector. To enable and enhance the energy efficiency, advanced control and optimization will play an important role in EV systems and infrastructure. However, there are also some difficulties and limitations subject to the imperfection of management and control for EVs. Overall, to further the widespread adoption of EVs, the dissertation mainly includes two parts: 1) Power management for Plug-in Hybrid Electric Vehicles (PHEVs); 2) Charging control for Plug-in Electric Vehicles (PEVs). Chapter 2 deals with the power management and route planning problems for PHEVs, which aims to properly design the control algorithm to find the route that leads to the minimum energy consumption. Chapter 3 pays attention to the high workloads of the PEV in the electric power grids, which concentrates on studying a control algorithm leading to possible reductions in both computation and communication. Chapter 4 focuses on the charging control for PEVs, which explores how to improve the PEV charging efficiency while satisfying safety concerns. Chapter 5 modifies the results in Chapter 4 by taking battery capacity degradation into the optimization problem. This dissertation proceeds with Chapter 1 by reviewing the state-of-the-art control methods for PEVs and PHEVs. Chapter 2 studies a novel control scheme of route planning with power management for PHEVs. By considering the power management of PHEVs, we aim to find the route that leads to the minimum energy consumption. The scheme adopts a two-loop structure to achieve the control objective. Specifically, in the outer loop, the minimum energy consumption route is obtained by minimizing the difference between the value function of current round and the best value from all previous rounds. In the inner loop, the energy consumption index with respect to PHEV power management for each feasible route is trained with Reinforcement Learning (RL). Under the RL framework, a nonlinear approximator structure, which consists of an actor approximator and a critic approximator, is built to approximate control actions and energy consumption. In addition, the convergence of value function for PHEV power management in the inner loop and asymptotical stability of the closed-loop system are rigorously guaranteed. Chapter 3 investigates the self-triggered Model Predictive Control (MPC) with Integral Sliding Mode (ISM) method of a networked nonlinear continuous-time system subject to state and input constraints with additive disturbances and uncertainties. Compared with the standard MPC strategy, the proposed control scheme is designed for PEV charging to reduce the high communication loads caused by a large-scale population of vehicles under centralized charging control architecture. In the proposed scheme, the constrained optimization problem is solved aperiodically to generate control signals and the next execution time, leading to possible reductions in both computation and communication. The motivation of using ISM approach is to reject matched uncertainties. A self-triggered condition that involves a comparison between the cost function values with different execution periods is derived. Besides, the robust MPC with ISM control strategy is rigorously studied depending on the self-triggered scheme. Chapter 4 proposes a charging control algorithm for the valley-filling problem, while it meets individual charging requirements. We study a decentralized framework of PEV charging problem with a coordination task. An iterative learning-based model predictive charging control algorithm is developed to achieve the valley-filling performance. The design of the decentralized MPC meets individual charging requirements. The iterative learning method approximates the electricity price function and the system state sampled safe set to improve the accuracy of optimization problem calculations. The decentralized problem, in which the individual PEV minimizes its own charging cost, is formulated based on the sum of all power loads. Chapter 5 studies a modified charging control algorithm based on the previous charging control algorithm in Chapter 4. We propose a charging control algorithm for PEVs using a decentralized MPC framework supplemented by the iterative learning method. By considering the battery aging of PEVs, we aim to find the optimal charging rate that leads to valley-filling performance. The scheme adopts the iterative learning-based method to solve the optimal control problem with the battery aging model. Specifically, the sampled safe set and price function are updated accordingly as the iteration number increases. The battery aging model involves the cost function to approach the real charging scenario. In addition, the recursive feasibility of the proposed optimal control problem for PEV charging with battery aging and asymptotical stability of the closed-loop system are rigorously studied. Finally, in Chapter 6, the conclusions of the dissertation and some avenues for future potential research are presented. / Graduate / 2023-04-07

The aim of this master thesis is to develop a suggested methodology for how to use Mavenoid infrastructure to improve customer support of DEFA EV chargers. Mavenoid is a company that helps other companies automate customer support, especially troubleshooting. This is done with Mavenoid models, interactive selfhelp tools that guide end users without technical knowledge through the troubleshooting process. Mavenoid models provide value both by deflecting cases (the end user solves the problem on their own using the model) and triaging cases (collect relevant information about the problem before escalating the case to a human support agent) The main methodology to develop a suggested methodology was learning by doing, using the suggested methodology to actually implement Mavenoid models available to end users on DEFA’s home page. This was complemented with a literature review, interviews and data analysis from model usage. The suggested methodology is to iteratively follow the steps of deciding which models to build, make priorities within these models, build the models, analyze their performance and continuously improve the models. To decide models, carefully evaluate DEFA’s support situation to decide where Mavenoid models would have the greatest impact. Force yourself to make quantitative assumptions to estimate a payback time for each possible model. For each model, carefully prioritize what to include and where the focus should be using estimates of frequency, value and time to model. Build the models to maximize deflection and triage and minimize abandoned sessions. Collect and analyze data from model usage and use this information to improve the models. To prioritize between possible improvements, force yourself to make quantitative assumptions of value and time to model and rank improvements by payback time. Limit the improvements you make either by time available or desired payback time. The potential business opportunity between Mavenoid and its customers is more attractive the more support cases the customer has and the larger fraction of end users that use Mavenoid. The business opportunity varies greatly with assumptions that are very difficult to estimate accurately at the early stages of a Mavenoid implementation. This indicates that Mavenoid models should be implemented step by step and assumptions updated when more data is available. Implementing Mavenoid models can be both positive and negative from a sustainable development perspective. They could encourage people to repair products instead of replacing them, scale renewable energy technology faster and remove boring and repetitive tasks from support staff. On the other hand, they might not be appreciated by all end users, could lead to increased electricity consumption and potential unemployment for support staff. Being about a largely unresearched topic, the results in this thesis are relatively subjective. This suggested methodology was used and proved to work to implement Mavenoid models for DEFA EV charging stations but it should be seen as one possible methodology, not the confirmed best methodology. / Syftet med detta examensarbete är att utveckla en metodologi för hur Mavenoids teknologi kan användas till att förbättra kundsupporten för DEFAs elbilsladdare. Mavenoid är ett företag som hjälper andra företag att automatisera kundsupport, särskilt felsökning. Detta görs med Mavenoidmodeller, interaktiva självhjälpsverktyg som guidar slutanvändare utan teknisk kunskap genom felsökningsprocessen. Mavenoidmodeller ger värde både genom att slutanvändaren löser problemet på egen hand genom att använda modellen (deflection) och genom att samla relevant information om problemet innan ärendet eskaleras till teknisk support (triage). Den huvudsakliga metoden för att utveckla metodologin var att lära genom att göra, faktiskt implementera Mavenoidmodeller och göra de tillgängliga för slutanvändare på DEFA: s hemsida. Detta kompletterades med en litteraturöversikt, intervjuer och dataanalys av hur modellerna användes. Den föreslagna metodologin är att iterativt följa stegen besluta vilka modeller som ska byggas, prioritera inom dessa modeller, bygga modellerna, analysera data från dem och kontinuerligt förbättra modellerna. För att bestämma modeller, utvärdera DEFAs supportsituation noggrant för att bestämma var Mavenoid-modellerna skulle ha störst inverkan. Tvinga dig själv att göra kvantitativa antaganden för att uppskatta en återbetalningstid för varje möjlig modell. För varje modell ska du noggrant prioritera vad du ska inkludera och var fokus ska vara genom att använda uppskattningar av frekvens, värde och tid att modellera. Bygg modellerna för att maximera deflection och triage och minimera övergivna sessioner. Samla och analysera data från modellerna och använd denna information för att förbättra modellerna. För att prioritera mellan möjliga förbättringar, tvinga dig själv att göra kvantitativa antaganden om värde och tid att modellera och rangordna förbättringar efter återbetalningstid. Begränsa de förbättringar du gör antingen utifrån tillgänglig tid eller önskad återbetalningstid. Den potentiella affärsmöjligheten mellan Mavenoid och dess kunder är mer attraktiv ju fler supportärenden kunden har och ju större andel slutanvändare som använder Mavenoid. Affärsmöjligheten varierar kraftigt med antaganden som är mycket svåra att uppskatta i början av ett projekt att implementera Mavenoidmodeller. Detta indikerar att Mavenoidmodeller bör implementeras steg för steg och antaganden uppdateras när mer data finns tillgängligt. Implementering av Mavenoid-modeller kan vara både positivt och negativt sett till hållbar utveckling. De kan uppmuntra människor att reparera produkter istället för att byta ut dem, skala upp förnybar energiteknologi snabbare och ta bort tråkiga och repetitiva uppgifter från teknisk support. Å andra sidan kanske de inte uppskattas av alla slutanvändare, kan leda till ökad elförbrukning och potentiell arbetslöshet för de som jobbar inom teknisk support. Eftersom examensarbetet handlar om ett relativt outforskat ämne är resultaten relativt subjektiva. Denna föreslagna metodologi användes och visade sig fungera för att implementera Mavenoidmodeller för DEFAs elbilsladdare men den bör ses som en möjlig metodologi, inte den bekräftat bästa metodologin.

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No description available.

This thesis consists of a comprehensive review of bidirectional charging technology, with focus on understanding the technical requirements and the challenges that has to be overcome to standardize this innovation. The thesis is based on three main objectives or goals that is needed to be able to answer the main review question which is: What does it take to standardize, develop and make bidirectional charging a reliable technology? The first objective is to review and explain how the technical bidirectional charging ecosystem works. It starts by explaining in detail how bidirectional charging works and looking closely at how the charging station, electric vehicle (EV), and the power grid connect and work together. The second objective consist of exploring the challenges and the benefits of bidirectional charging. The main challenges explored are social challenges, regulatory challenges, technical challenges and battery degradation. The main benefits explored in this thesis are: offloading the power grid, environmentally friendlier benefits, economic benefits and better management of renewable home systems. The third and final objective in this thesis covers a surveying of existing bidirectional charging products and solutions like Fords F-150 lightning V2G technology and CHAdeMO 2.0. Explaining what they are and their potential success in the European market. The thesis concludes by addressing and discussing the central researched question, which indicates that bidirectional charging is still a young technology that needs to overcome many challenges and improve in some areas before it can be widely used by consumers in a safe and effective way. The results show that the speed and success of the development of this technology depend on how well the actors and stakeholders cooperate with each other and how fast the regulations and standards evolve. EU and Swedish regulations need to keep developing standards for better interoperability. This will help create a legislation for independent market players and key stakeholders, making it easier for them to interact and make compatible products. Therefore, the research done in this thesis suggests that in order to standardize bidirectional charging, different actors, stakeholders and regulatory organizations need to work together better in the future to make V2X safe, standardized and interoperable. There are very few V2G solutions available for customers today, but with the cooperation of key actors, new ISO standards and EV manufacturers making more compatible cars, this technology has the potential to become more accessible in the upcoming years.

The global shift towards Electric Vehicles (EVs) is driven by their energy efficiency, lower emissions, and reduced dependence on fossil fuels. As the demand for EVs continues to rise, the need for EV ultra-fast chargers becomes paramount to enable faster charging times and facilitate long-distance travel without compromising convenience. In this context, solid-state transformers (SSTs) have emerged as a promising technology to replace traditional line-frequency transformers (LFTs) in various applications, including EV charging stations. SSTs offer improved system controllability, power factor correction capabilities, and reduced size and weight through the utilization of medium-frequency transformers (MFTs). This thesis focuses on enhancing the efficiency and power density of the MFT used in SSTs. A 1.2 MVA SST for EV ultra-fast charging stations is designed and simulated. The SST incorporates average controllers responsible for regulating the output voltage and the input power factor, as well as, voltage and power balancing controllers to ensure stable operation among its cells. Furthermore, a design methodology for optimizing the MFT used in DC-to-DC converters for SST-based ultra-fast chargers is introduced. The methodology is optimizing the efficiency and power density of the transformer based on the transformer parameters input by the designer. A software tool is developed to streamline the design process and enable the optimization of various parameters, such as core material, size, and winding configurations. The tool facilitates the development of high-performance MFTs for SST applications. The developed MFT optimization methodology is utilized to design a 100 kW, 20 kHz MFT, resulting in a remarkable 22.7% improvement in power density compared to conventional design methods. The transformer showed superior efficiency and power density compared to MFT designs in literature. Additionally, two scaled-down transformers are designed and tested at 5 kW, employing both conventional and optimization methods. The results demonstrate a significant 57.8% improvement in specific power. / Thesis / Master of Applied Science (MASc)

Electric vehicle (EV) adoption continues to rise, yet EV sales still represent a small portion of vehicle sales in most countries. An expansion of the DC fast charging (DCFC) network is likely to accelerate this revolution towards sustainable transportation, giving drivers more flexible options for charging on longer trips. However, DCFC presents a large load on the grid which can lead to costly grid reinforcements and high monthly operating costs – adding energy storage to the DCFC station can help mitigate these challenges. This thesis first performs a comprehensive review of DCFC stations with energy storage, including motivation, architectures, power electronic converters, and detailed simulation analysis for various charging scenarios. The review is closely tied to current state-of-the-art technologies and covers both academic research contributions and real energy storage projects in operation around the world. It is identified that the battery energy storage systems (BESSs) with active front end converter provides high efficiency with reasonable power density in a DCFC station. It is also realized that the isolated DC/DC converter interfacing BESS and EV determines the overall efficiency of a DCFC station with a low grid connection. Secondly, this thesis analyzes the impact of active front end based DCFC stations connected to a grid distorted with background voltage harmonics. In active front end based DCFC stations, background voltage harmonics produce current not only at the frequencies of the distorted voltage, but also at other coupled frequencies. Various mitigation techniques, such as increasing inner control loop gain, grid voltage feedforward, and selective harmonic compensation, have been adopted in industry to reduce the emissions originating from distorted background voltage. However, although these techniques are effective in suppressing the current at the harmonic orders present in the background voltage, they deteriorate the emission at coupled frequencies. This thesis provides the theoretical explanation of this phenomenon, which is verified by simulation of a two-level active front end in PSCAD/EMTDC. This thesis also discusses the proper treatment of current emission due to background voltage harmonics. Thirdly, the thesis identifies the semi dual active bridge (semi-DAB) converter as an ideal candidate as the interfacing isolated DC/DC converter between the BESS and the BEV. A novel control strategy is proposed for the semi-DAB converter to achieve wide voltage gain while increasing the efficiency at operational points with high input voltage and low output voltage, which is a commonly occurring scenario when the BESS is fully charged, and the EV battery is at low charge. Furthermore, this thesis also provides an algorithm to determine the required phase-shift in real time for any operating point, eliminating the need to devise the control trajectory offline. A 550 V, 10 kW experimental prototype is built and tested to validate the proposed control strategy. With a 25 A constant charging current, the prototype shows the proposed control strategy can improve efficiency by up to 3.5% compared to the well-known dual phase shift control at operating points with high input voltage (450 – 550 V) and low output voltage (150 – 275 V), with a peak efficiency of 97.6%. Finally, this thesis proposes a novel variable turns-ratio semi-DAB converter to improve its overall efficiency even further when the input voltage is high and the output voltage is low. Furthermore, a control law is also proposed to determine the turns-ratio, i.e., the operational structure of the converter, which reduces the converter peak and rms current. The 550 V, 10 kW prototype is modified to accommodate the variable turns-ratio high frequency transformer to test the proposed converter and control. The proposed converter with control can further improve the efficiency at many operating points compared to single turns-ratio semi-DAB with DPS control. The peak efficiency achieved is 98.5%. / Thesis / Doctor of Philosophy (PhD)

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Analytical and numerical studies are carried out to investigate spacecraft charging and plasma interactions in the solar wind. The physics of spacecraft charging in solar wind is determined by the mesothermal flow and the photoelectron sheath. In order to properly resolve both plasma flow and the photoelectron sheath, a 3-D full particle PIC model is applied. In this model, all plasma species (ambient ions and electrons, and photoelectrons) are modeled as macro-particles so the detailed dynamics of each species can be resolved around a charged spacecraft. In order to correctly resolve the mesothermal velocity ratio, PIC simulations are carried out using the real ion to electron mass ratio. A charging model based on the capacitance matrix method is integrated into the PIC model so the floating potential can be calculated self-consistently with the PIC code from charges deposited on the surface. We first investigate the photoelectron sheath in the solar wind. Previous analytical studies of monotonic and non-monotonic sheath profiles in stationary electrons have suggested that there can exist two solutions of the sheath profiles when photoelectron emissions are significant. We extend the previous analytical approach to include the effects of drifting electrons. Full particle PIC simulations suggest that the non-monotonic sheath profile is the stable solution under solar wind conditions. We found that the current balance calculation is not an accurate method to predict the floating potential when photoelectron emissions are significant. We next apply the simulation model to study spacecraft charging under various solar wind conditions. Due to photoelectron emissions, spacecraft charging is typically not a serious problem. The floating potential is ~2.5V under the mean solar wind condition. We also investigate the plasma interactions of a multi-body system consisting of a large platform and a small free flyer in the absence of photoelectron emissions where we set a free flyer at 2*Debye length behind the platform in the wake. For the particular system studied in this dissertation, the simulation shows that wake charging is not severe under both the mean solar wind condition and severe magnetosheath charging condition. / Ph. D.

This thesis seeks to understand the relationship between government influence and market forces pertaining to the introduction of new technologies in the market. The thesis will do this by utilizing electric vehicle supply equipment (EVSE) in California and Virginia as a historical analysis case study to determine the historical catalysts for change in the public EVSE market since its introduction in 1995. Comparing the rate of change to historical timelines for both states, "market tendencies" and "government involvement" played the greatest role in EVSE growth, with there being a distinct shift from "market tendencies" to "government involvement" over time. Results show that California has fully embraced the interventionist role, with state and local actors playing a part. Virginia, on the other hand, has just begun to allow state intervention, so much of the change in the state has come from economic or business events. Data shows, however, that this could be changing, and that Virginia could be on the verge of allowing for market intervention based on equitable development and future economic opportunity. / Master of Arts / The 21st century is ripe with innovative technologies and ideas that influence the future of the world, but not all these ideas are fully embraced in the private market. This thesis looks to understand the different roles that the government can play in assisting with the development of markets by analyzing the introduction of electric vehicle supply equipment (EVSE) for public use in California and Virginia. Using a historical-analytic approach, I gathered data on the rate of increase in EVSE and compared that to the historical timelines to determine the variables with the most influence. After identifying four "pivotal moments" in the timeline, I discovered that the major catalysts for change were "market tendencies" and "government involvement." Looking at the progression, I determined that there is a distinct trend shifting from market tendencies, at the beginning of the timeline, to government involvement in modern changes. Evidence shows that not only is this trend embraced in California, with many state and local bodies working on the issue, but it also shows that Virginia, the laggard of the two states, could be on the verge of straying from its ideals of "free markets" to embrace change.