A Game-Based Battery Swapping Station Recommendation Approach for Electric Vehicles

Abstract

It is of great significance to develop a coordinated battery swapping station (BSS) recommendation method to reduce the cost of electric vehicles (EVs) and optimize the operation of BSS system. In this paper, the BSS recommendation problem is studied by comprehensively considering the battery swapping cost, diversity of BSS capacities, and differentiated demands of EVs, so as to be as close to the actual situation as possible. To describe the interactions among EVs, we propose a game theory-based approach to recommend appropriate BSSs for EVs to minimize the total cost (namely the sum of travel cost and battery swapping cost) of each EV. Under the game framework, a price function is designed to regulate the swapping price of each BSS, which acts as a coordination signal to induce EVs to join the game and also to alleviate congestion of BSSs. Then, an iterative algorithm is devised to seek the Nash equilibrium, through which a suitable BSS is determined for each EV. Compared to the shortest distance approach, the case studies indicate that the proposed approach can effectively reduce the average cost of EVs, improve the success rate of battery swapping, and balance the utilization ratio of BSSs.