Electric Vehicle Charging Path Scheduling Using Real-Time Road Network Data

With the increasing number of electric vehicles, the "range anxiety" issue caused by limited driving distance has become a significant concern for users. To address users' concerns about insufficient battery power during trips and to improve charging facility utilization, this paper presents an electric vehicle charging path scheduling approach that comprehensively takes into account driving time, queuing time, and charging time. The proposed method integrates real-time road network topology information with the Dijkstra shortest path algorithm, assisting users in planning charging routes and choosing charging stations. A case study involving a real-world road network in a specific area of Wuhan is conducted, including simulation analysis with a given number of electric vehicles. The results indicate that, compared to conventional uncoordinated scheduling methods, the proposed strategy effectively decreases users' overall charging time cost and enhances the efficiency of charging station usage.