Optimizing dynamic wireless charging for electric buses: A data-driven approach to infrastructure planning

Sun, Ruixiao; Luo, Qi; Chen, Yuche

doi:10.1016/j.apenergy.2024.123912

Optimizing dynamic wireless charging for electric buses: A data-driven approach to infrastructure planning

Journal Article · Wed Jul 17 00:00:00 EDT 2024 · Applied Energy

DOI:https://doi.org/10.1016/j.apenergy.2024.123912· OSTI ID:2406720

Sun, Ruixiao ^[1]; Luo, Qi ^[2]; Chen, Yuche ^[3]

Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
University of Iowa, Iowa City, IA (United States)
Univ. of South Carolina, Columbia, SC (United States)

The network configuration significantly impacts the performance of dynamic wireless charging (DWC) technology for electric buses. Here, this study presents a novel approach to planning charging infrastructure for public transit using data-driven nonconvex mixed-integer optimization. Integrating DWC and charging station technologies reveals a trade-off between enroute and stationary charging times. Our framework optimizes bus frequency settings and transmitter coil arrangements to minimize operational and infrastructure costs. A case study in Chattanooga, Tennessee, demonstrates the method's effectiveness in mitigating range anxiety and reducing charging expenses. This research implies that integrating DWC technology into public transit systems can enhance the feasibility and cost-effectiveness of electric bus operations, promoting sustainable urban mobility.

View Accepted Manuscript (DOE)

Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE)

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 2406720

Journal Information:: Applied Energy, Journal Name: Applied Energy Vol. 373; ISSN 0306-2619

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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