Mobile autonomous pods for electric vehicle charging operations

QC 20250915

Abstract

This thesis investigates innovative approaches to electric vehicle (EV) charging by addressing key research gaps identified through a systematic literature review on EV charging technologies. In particular, it focuses on the potential of Vehicle-to-Vehicle (V2V) charging using Mobile Autonomous Charging Pods (MAPs), which are autonomous battery electric vehicles capable of transferring stored energy to other EVs while in motion or during short stops. To evaluate their feasibility and performance, a simulation-based framework is then developed using the Simulation of Urban Mobility (SUMO) platform.

The thesis addresses three central research questions: (a) how various charging technologies compare in terms of initial investment, deployability, flexibility, scalability, technological maturity, and their implications for travel time and battery sizing; (b) how MAPs can be effectively deployed to serve electric vehicle fleets; and (c) how MAPs can be integrated into urban bus networks to reduce infrastructure investments, minimize battery capacity requirements, and lower the total cost of ownership.

Paper I presents a framework that categorizes EV charging methods into stationary and dynamic (in-motion) solutions. This framework emphasizes the need for dynamic charging strategies and critically evaluates dynamic charging technologies, such as charging lanes, vehicle-to-vehicle (V2V) charging, and dynamic battery swapping, comparing infrastructure costs, battery capacity reduction, and scalability. The study also identifies various research gaps and future research directions for dynamic charging stations. The review underscores that a hybrid strategy, integrating both conventional and dynamic charging, may best meet future energy demands. Moreover, the research emphasizes the importance of optimization models for infrastructure deployment, the need to balance battery capacity reduction with battery life preservation, and the development of interoperability standards to ensure seamless integration with emerging autonomous technologies. These contributions not only advance academic understanding but also offer practical guidance for policymakers, transit planners, and industry stakeholders seeking to enhance the sustainability and efficiency of modern transportation systems.

Paper II introduces a dynamic mobile charging strategy using MAPs. Through microscopic simulation with SUMO, this research evaluates the feasibility and benefits of the proposed approach in facilitating continuous autonomous electric vehicles (eAV) operation based on the maximum number of eAVs served on a toy network, energy consumed, charging efficiency of MAPs, and reduced travel time compared to stationary charging. Results indicate that MAPs may effectively support eAVs in driving continuously by providing on-the-go charging, thereby reducing the need for large battery capacities in eAVs, thus reducing weight and cost. The study also identifies potential use cases and locations where MAPs will have greater benefits, the economic and operational benefits of MAP deployment, while outlining potential barriers and future research directions in optimization and control.

Paper III evaluates charging strategies for urban bus networks using a simulation-based approach focused on Stockholm’s inner-city bus lines. It compares various charging strategies for electric buses including depot-only charging, depot combined with end-station charging, and depot augmented by MAP charging. The findings indicate that MAP-based dynamic charging substantially reduces both required battery size, infrastructure costs, and total cost of ownership, while enhancing service reliability.

Collectively, these studies provide a systematic assessment of EV charging methods and highlight the potential of dynamic charging, particularly through MAPs, in developing sustainable and efficient transportation systems.

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