Optimizing In-Motion Wireless Charging Service Efficiency for Electric Vehicles: A Game Theoretic Approach

With the application of Wireless Power Transfer (WPT) techniques for Electric Vehicles (EVs), public transportation EVs are expected to be continuously operable without recharging downtime. A road segment equipped with an inmotion wireless charger is called a charger lane. To maximize the service efficiency of deployed in-motion wireless chargers without suffering from traffic congestion, we must properly manage the traffic of the EVs and coordinate their arrivals at the charger lanes to avoid the generation of traffic congestion at the charger lanes and on the road segments to them. In this paper, we propose WPT-Opt, a game theoretic approach for Optimizing in-motion wireless charging service efficiency, minimizing EVs' time spent on the way to the charger, and avoiding traffic congestion at the charger lanes, to fulfill this task. We studied a metropolitan-scale dataset of public transportation EVs, and observed the EVs' spatial and temporal preference in selecting chargers, competition for chargers during busy charging times, and the relationship between vehicle density and driving velocity on a road segment. Then, we formulate a non-cooperative Stackelberg game between all the EVs and a central controller, in which each EV aims at minimizing its charging time cost to its selected target charger, while the central controller tries to maximally avoid the generation of congestion on the in-motion wireless chargers and the road segments to them in the near future. Our tracedriven experiments on SUMO demonstrate that WPT-Opt can maximally reduce the average charging time cost of the EVs by approximately 200% during different hours of a day.