Enabling the Wireless Charging via Bus Network: Route Scheduling for Electric Vehicles

• Published in: IEEE transactions on intelligent transportation systems Vol. 22; no. 3; pp. 1827 - 1839
• Main Authors: Jin, Yong, Xu, Jia, Wu, Sixu, Xu, Lijie, Yang, Dejun
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.03.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; bus network; Buses (vehicles); Charging stations; Electric power grids; electric vehicle; Electric vehicle charging; Electric vehicles; Inductive charging; Intelligent transportation system; maximum weighted matching; Residual energy; restricted shortest path; Roads; Routing; Schedules; Scheduling; Traffic conflicts; Traffic congestion; Transportation networks; Travel time; Urban areas; wireless charging; Wireless power transmission
• ISSN: 1524-9050; 1558-0016
• DOI: 10.1109/TITS.2020.3023695

The development of Electric Vehicle (EV) helps to ease energy crises and deduce vehicle exhaust emissions. However, it also brings a great impact on both transportation networks and power grids. There are some serious impediments in terms of energy charging to the popularization of EV, such as high deployment cost of charging stations, low charging efficiency, and voltage deviation of power grid. To address these issues, we design a new EV charging system, which levers the bus network in urban areas through the integration of OnLine Electric Vehicle (OLEV) system and Microwave Power Transfer (MPT) system. We formulate the EV route scheduling problem based on this new charging system to maximize the total residual energy subject to all EVs can arrive to their destinations before deadlines. Then, we propose an approximation algorithm, RSA , to solve the route scheduling problem. To relieve the traffic congestion, we further formulate the conflict-free EV route scheduling problem, and use the matching based algorithm, FRSA , to find the EV route schedules with the maximal residual energy. Through the extensive simulations, we demonstrate that RSA and FRSA can increase the average residual energy by 67.66% and 50.36% compared with the solution without the designed wireless charging system, respectively. Moreover, RSA reduces 22.22% of travel time and outputs 77.23% of residual energy, and FRSA can obtain 83.51% residual energy with 3.62% of extra travel time of the corresponding optimal solutions on average, respectively.