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<p dir="ltr">The rising demand for EVs, motivated by their environmental benefits, is generating increased need for EV charging infrastructure. Also, it has been recognized that the adequacy of such infrastructure helps promote EV use. Therefore, to facilitate EV adoption, governments seek guidance on continued investments in EV charging infrastructure development. The high cost of these investments motivates governments to seek optimal decisions on EV-related investments including EV charging infrastructure, and such decisions include locations, capacities, and deployment scheduling of such infrastructure. Additionally, uncertainties in travel demand prediction and EV driving range constraints need to be considered in EV infrastructure investment planning. To help address these questions, this thesis developed a framework to establish optimal schedules and locations for new charging stations and for decommissioning gasoline refueling stations for any given network over a long-term planning horizon, considering uncertainties in travel demand forecasts and EV driving-range heterogeneity. To address the uncertainties, the proposed framework is formulated as a robust mathematical model that minimizes the worst-case total system travel cost and the total penalty for unused charging station capacity. This study uses an adaption of the cutting-plane method to solve the proposed model. In the numerical analyses, the performance of the robust framework and its deterministic counterpart are compared. The results show that the optimal robust plan outperforms the deterministic plan by yielding savings in the costs of travel and electricity charging. The thesis also investigates the effects of investment budget levels of robust planning. The numerical results throw light on the relationships between higher investment levels and electric charging station deployment levels and consequently, the savings in travel costs and impacts on unused charging capacity. The outcomes of this thesis can help road agencies and related private sector entities enhance preparations towards infrastructure investments to support electric charging stations in an efficient manner.</p>

Yes / This paper presents a robust framework for active and reactive power management in distribution networks using electric vehicles (EVs). The method simultaneously minimizes the energy cost and the voltage deviation subject to network and EVs constraints. The uncertainties related to active and reactive loads, required energy to charge EV batteries, charge rate of batteries and charger capacity of EVs are modeled using deterministic uncertainty sets. Firstly, based on duality theory, the max min form of the model is converted to a max form. Secondly, Benders decomposition is employed to solve the problem. The effectiveness of the proposed method is demonstrated with a 33-bus distribution network.

Transportation and energy play an essential role in modern society. Since the Industrial Revolution, fossil fuels have enabled great advancements in human society. Within this process, Internal Combustion Engines Vehicles (ICEVs) played a significant role in guaranteeing reliable and affordable long-distance transportation. However, the subsequent increase of the Motorized Private Transport resulted in undesired effects such as pollution. One instrument in reducing the Greenhouse Gas (GHG) emissions of the transport sector is to shift from the conventional ICEVs toward zero local emission vehicles. Electric Vehicles (EVs) are being promoted worldwide as a suitable powertrain technology that could replace the ICEVs. However, unless combined with electricity from renewable generation technologies the EVs will not effectively reduce GHG emissions. Through the simulation of future transport and energy sector scenarios in Germany, the GHG emission reductions have been analyzed. Techno-economic and environmental characteristics for several powertrain technologies under several vehicles charging strategies are evaluated. The thesis explores the impact of charging EVs on the electrical grid. The result show that EVs using smart charging strategies that support Vehicle-to-grid (V2G) are capable of fulfilling mobility needs of users while providing substantial flexibility to the electrical grid. Such flexibility can facilitate the future expansion of non-dispatchable Renewable Energy Sources (RES).

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>

This study delves into the comparative operational effectiveness of non-coordinated, bottom-up, and top-down coordinated control models within Distributed Energy Storage Systems (DESS) and Electric Vehicle (EV) networks. Employing meticulous data analysis, this research evaluates power demand and supply dynamics within the infrastructure and buildings, aiming to optimize energy usage and storage. The analysis involves comprehensive steps: descriptive statistical breakdown, understanding energy patterns across buildings, and a comparative assessment of the control models. Visual representations and graphs aid in depicting energy patterns, emphasizing the distinctive characteristics and effectiveness of each control model. The findings reinforce the superiority of the top-down coordinated control model in managing supply-demand imbalances, echoing established literature.

<p>  </p> <p>The trucking industry seems to be resistant to electrification, even though truck electrification can lead to large societal as well as user benefits. This dissertation develops a framework to inform policy making and enhance electric vehicle (EV) preparedness in the trucking industry through the study of two interrelated elements: (a) the adoption of electric trucks and (b) the appropriate implementation of electric truck technology. These two elements cover the user perspective, which is not adequately studied, and the agency perspective, which is pivotal in the decision-making process. Specifically, this study addressed the following research questions: (i) which factors affect the purchase decisions of truck fleet managers or owners for electric trucks? (ii) what is the ranking of and interrelationships between the barriers to the adoption of electric trucks? (iii) which location criteria should be considered for the strategic implementation of dynamic wireless charging (DWC) in a freight transportation network and where should this technology be located based on these criteria, and (iv) what is the impact of electric truck adoption on highway revenue and potential of alternative funding mechanisms to recover the revenue loss?</p> <p>For the adoption of electric trucks, a stated preference survey was designed and distributed online to truck fleet managers/owners in the U.S., gathering 200 completed responses. Statistical and multi-criteria decision-making approaches were employed to identify the factors that affect the purchase intentions of truck fleet managers and explore the barriers to electric truck adoption. The results showed that the purchase intentions of truck fleet managers are affected by trucking firm and truck fleet characteristics, behavioral factors/opinions regarding electric trucks, and awareness of innovative charging technologies. Furthermore, electric truck adoption would be accelerated if stakeholders focused on the barriers related to the business model, product availability, and charging time. Additionally, electric truck adopters and non-adopters may not be viewed as one homogenous group, since differences were found in the ranking and interrelationships of barriers to electric truck adoption between these two groups. </p> <p>The implementation of electric truck technology was examined based on the truck fleet managers’ survey, secondary data sources and the case of Indiana, U.S. A multi-criteria decision-making spatial approach was proposed to identify the candidate locations for the deployment of DWC. It was concluded that the most suitable locations for DWC lanes were on interstates, near airports and ports and away from EV charging stations. A data-driven framework was also developed to quantify the impact of electric truck adoption and estimate the optimal fee for each truck to recover the revenue loss. Using the market penetration levels estimated based on the survey data collected, the average annual fuel tax revenue loss for Indiana was approximately $349M. To maintain the same tax revenue per vehicle, annual fees ranging from $969 (in 2021) to $1,243 (in 2035) for single-unit trucks and $6,192 to $7,321 for combination trucks would be needed. To address public relations problems of EV fee implementation, this study also discussed alternative mitigation measures: a vehicle-miles-traveled fee and a pay-as-you-charge fee.</p> <p>In summary, this dissertation contributes to the body of literature by providing significant insights regarding the perspectives of truck fleet managers for electric trucks as well as a comprehensive list of all the location criteria for DWC. The proposed frameworks and study findings can be used by policymakers and other major stakeholders of the EV ecosystem to frame certain strategies to accelerate electric truck adoption, identify the most suitable locations for charging infrastructure, better understand the impact of electric trucks on the highway revenue, and provide the groundwork for developing EV roadmaps.</p>

The demands for sustainable transportation have made battery electric vehicles an increasingly popular subject in the world of both businesses and engineering. This thesis has been made in collaboration with Scania, which is currently investigating the possibility of manufacturing stators and rotors in-house in a series production line. For Scania, the topic of quality assurance is of great importance as Scania wants to ensure their trucks and buses fulfil the quality requirements of both customers and society. The goal of the thesis is to provide Scania with a set of guidelines for what quality assurance steps to perform in a series stator winding production, and where in the production they should be placed. The investigated stator winding type is a continuous hairpin winding, and the investigated quality assurance steps are solely electrical tests used to ensure the safety, functionality, and quality of the stator windings. A process-failure modes and effects analysis were conducted to identify the risks associated with each production step. The results indicates where the quality assurance steps should be taken. Further analysis, based on the provided background of electrical tests, also provides an answer to what electrical tests to perform as quality assurance steps. The result of the thesis is a concept, presented in a flow chart diagram, which indicates what electrical tests to perform and where the tests should be performed in the stator winding production chain. / De krav som sätts på hållbar transport har gjort batteridrivna elektriska fordon ett alltmer populärt ämne i världens företag och ingenjörskonst. Denna avhandling har gjort i samarbete med Scania, som i nuläget utreder möjligheterna för att tillverka statorer och rotorer in- house i en serie produktionslinje. För Scania är ämnet kvalitetssäkring (QA) ett viktigt ämne, för att Scania vill säkerställa att deras lastbilar och bussar lever upp till de kvalitetskrav som både kunder och samhället ger. Avhandlingens mål är därför att förse Scania med en uppsättning av riktlinjer för vilka QA steg som ska utföras i en serie statorlindningsproduktion, och var i produktionen de ska placeras. Den statorlindningstypen i fokus är en kontinuerlig hårnålslindning, och att de kvalitetssäkringar som undersöks är enbart elektriska test som säkrar säkerhet, funktionalitet samt kvalitén av statorlindningarna. En P-FMEA har utförts som en risk och felläges analys i syfte att identifiera de risker som är associerat med varje produktionssteg. Resultatet pekar på var QA steg ska utföras någonstans. Fortsatt analys, baserat på den givna bakgrunden av elektriska test, ger även ett svar på vilka elektriska test som ska utföras som QA steg. Avhandlingens resultat är ett koncept, presenterat i ett flödesdiagram, som visar vilka elektriska test som ska utföras samt var dessa tests ska utföras i statorlindningsproduktionen.