<p dir="ltr">Electric roadways (ERs) represent a new paradigm for electrified transportation that is</p><p dir="ltr">enabled by the emerging dynamic (in-motion) wireless power transfer technology. Large-scale</p><p dir="ltr">integration of DWPT systems into power grids can pose a problem due to its high-power</p><p dir="ltr">requirements, significant number of power electronic converters and spatial concentration.</p><p dir="ltr">Despite their potential magnitude, the operational impacts of DWPT on the power grid have</p><p dir="ltr">not been fully studied in the literature. This dissertation contributes to our understanding</p><p dir="ltr">of how ERs could be successfully integrated with the electric power system at a diverse range</p><p dir="ltr">of spatial and temporal levels.</p><p dir="ltr">On a macroscopic level, a framework for assessing the financial viability of ERs is proposed.</p><p dir="ltr">Annual ER load estimations from traffic flow models of electric vehicles are used to</p><p dir="ltr">generate energy forecasts and carry out a financial evaluation. These models are also used to</p><p dir="ltr">plan distribution system capacity expansion. On a mesoscopic level, a data-driven design of</p><p dir="ltr">ERs and their interconnection with the distribution grid is presented. A data-based stochastic</p><p dir="ltr">traffic flow model is developed and used for designing the interconnection of the DWPT</p><p dir="ltr">system with the distribution grid ensuring adequate power transmission to high penetration</p><p dir="ltr">levels of heavy-duty trucks. The model is also used for conducting a series of quasi-steady</p><p dir="ltr">state studies on the power distribution system. On a microscopic level, a methodology for</p><p dir="ltr">modeling ER systems for time-domain simulations is proposed. Dynamic component models</p><p dir="ltr">are developed for the DWPT system. Power electronics are modeled using average-value</p><p dir="ltr">representations and integrated with models of the distribution grid. The models are used for</p><p dir="ltr">time-domain system simulations, transient analysis, fault analysis and power quality studies.</p><p dir="ltr">Theoretical analysis as well as numerical case studies and simulations of the proposed</p><p dir="ltr">methodologies are presented.</p>

<p dir="ltr">In this thesis, a MATLAB model was used to simulate a 2-vehicle platoon where the lead truck is a conventional class 8 vehicle while the key parameters of the following truck was tested in various road conditions to minimize Inter vehicular Distance (IVD) and maximize fuel savings while ensuring safety</p>

<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>

<p dir="ltr">In our daily lives, we rely on a multitude of discrete products to meet our needs. Traditional product design approaches have primarily focused on economic and technical aspects, often overlooking the pressing environmental and social challenges facing society. Recognizing the limitations of our ecological systems to cope with the waste generated by our current industrial processes, there is a growing need to anticipate the potential consequences of product design across technical, economic, environmental, and social dimensions to pave the way for a sustainable future. One promising strategy within this context is the integration of sustainability principles into optimization-based design models that consider a product's entire life cycle. While there have been previous efforts to optimize product life cycles, a comprehensive exploration of optimization-based design methods with a focus on multiple objectives for discrete products is essential. This dissertation explores the integration of sustainability principles with optimization-based design by taking the electric traction motor used in electric vehicles as a case study. This complex and environmentally significant technology is ideal for investigating the tradeoffs and benefits of incorporating sustainability objectives into the design process.</p><p dir="ltr">The key tasks undertaken in this study are as follows:</p><ul><li>Development of a parametric design and optimization framework for a surface-mounted permanent magnet synchronous motor. In this task, a special emphasis is placed on reducing reliance on materials with a high supply risk, such as rare earth elements.</li><li>Creation of a parametric life cycle assessment model that combines life cycle assessment and optimization-based design to minimize a single-score environmental impact. This model offers insights into the environmental performance of product design and underscores the importance of minimizing environmental impact throughout a product's life cycle.</li><li>Integration of a life cycle costing model, incorporating techno-economic assessment and total cost of ownership perspectives, into the parametric life cycle assessment and optimization-based design models. This model is used to minimize levelized production and driving costs, shedding light on the trade-offs within this family of cost metrics and the optimization of manufacturing systems for motor production.</li><li>Proposal of a circular economy model/algorithm to assess the advantages of integrating the circular economy paradigm during the early design phase. All the mentioned objective functions are considered to study the impacts of applying the circular economy paradigm.</li></ul><p dir="ltr">The contributions of this research can be summarized as follows:</p><ul><li>Utilized a diverse array of analytical methodologies to parameterize the design process of a motor, incorporating the integration of Life Cycle Assessment (LCA) and Techno-Economic Analysis (TEA) models, as well as the incorporation of disassembly planning for informed decision-making in the early stages of design.</li><li>Proposed a generalized objective function denoted as the Supply Risk-equivalent (SR-eq.), aimed at mitigating the risks associated with the dependency on critical materials in product manufacturing.</li><li>Introduced a novel approach for visualizing non-dominated solutions within a multi-objective framework, with experimentation conducted on up to six distinct objectives.</li><li>Substantiated the significance of decarbonizing the electric grid while maintaining competitive cost structures, the importance of advancing non-destructive evaluation (NDE) procedures for assessing the condition of end-of-life (EoL) subassemblies, and optimizing the collection rate of EoL motors.</li></ul><p dir="ltr">Demonstrated that the optimization of technical metrics as surrogate indicators for economic and environmental performance does not necessarily yield designs that are concurrently optimal in economic and environmental terms.</p>