Locational Analysis of In-motion Wireless Power Transfer System for Long-distance Trips by Electric Vehicles: Optimal Locations and Economic Rationality in Japanese Expressway Network

Yudai Honma (), Daisuke Hasegawa, Katsuhiro Hata and Takashi Oguchi
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Yudai Honma: The University of Tokyo
Daisuke Hasegawa: The University of Tokyo
Katsuhiro Hata: The University of Tokyo
Takashi Oguchi: The University of Tokyo

Networks and Spatial Economics, 2024, vol. 24, issue 1, No 9, 290 pages

Abstract: Abstract The popularization of electric vehicles (EVs) is limited by their driving range and long charging times. To address this, in-motion wireless power transfer systems (WPTSs) are currently attracting attention as a new power supply system. In-motion WPTSs have coils embedded under the road to transfer power from the WPTSs to EVs while driving. However, the main drawback of WPTSs is their large investment, especially in supporting the long-distance trips of EVs on expressways. Therefore, this study proposes a new mixed-integer programming model (MIP) to determine the optimal location of WPTSs for maximized total feasible flow demand. By focusing on long-distance trips on expressways, we propose the first flow-capturing model for WPTS locations that can (i) solve for the distance of WPTS installed as continuous variables, and (ii) solve problems based on real-scale data using a general MIP solver. Our method is extended to a discussion of WPTS installations on expressways in Japan. We observe that WPTS has strong potential as an EV power supply system in terms of coverage and economic rationality. In particular, WPTS has economic rationality not only in busy networks but also in sparsely populated networks that connect urban and rural areas. Thus, this study clarifies the important insights of WPTSs in improving their effectivity to narrow down the demand and ensure the flexibility in the locations of WPTS.

Keywords: Electric vehicle; Charging infrastructure; In-motion wireless power transfer; Mixed integer programing; Intelligent transportation system (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11067-023-09608-w

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