Joint Routing and Wireless Charging Scheduling for Electric Vehicles With Shuttle Services
Yongsheng Cao, Yongquan Wang, Demin Li, Xuemin Chen
Abstract
As the electric vehicles (EVs) become prevalent, the demand for smart charging rises. The disordered charging problem of EVs, the high cost, and the location problem of charging stations bring a great challenge to the power grids and transport networks. The Internet of Things (IoT) technology enables the IoT-based EV (IoEV) to plan the route and process the information with smart wireless charging. However, how to schedule the optimal routing and wireless charging is challenging. In this article, we consider a joint routing and wireless charging scheduling problem with a microwave power transfer system to minimize the travel distance, the charging cost, and battery degradation cost when IoEVs provide shuttle services. To solve this mixed linear programming problem for the joint routing and charging schedule of IoEVs with the integer routing variables and continuous charging variables, we propose a routing and charging customized benders decomposition (RCBD) algorithm. To increase the time efficiency of the RCBD algorithm, we propose an improved RCBD (IRCBD) algorithm with the trajectory similarity measurement method. Extensive simulation results show the effectiveness and correctness of the proposed scheduling algorithms. We compare the IRCBD algorithm with the actor–critic algorithm and the RCBD algorithm. The charging cost of the IRCBD algorithm with the threshold 0.9 of trajectory similarity is 5.56% more than that of the RCBD algorithm. The running time of the IRCBD algorithm is 50.01% less than that of the RCBD algorithm when there are 300 pickups and deliveries. The running time of the IRCBD algorithm is less than that of the RCBD algorithm and the actor–critic algorithm.