A Bayesian Game Based Bidding Scheme for Mobile Charging Services in IoEV

Due to the low cost and agile service provision, mobile charging stations (MCSs) have been deployed to complement fixed charging stations (FCSs). In the Internet of Electric Vehicles (IoEV) with MCSs, a major concern is to enhance the charging efficiency of MCSs. The charging efficiency of MCSs can be improved by prolonging the charging durations of MCSs, i.e., MCSs should undertake the charging tasks as more as possible, which can increase the charging profits of MCSs and reduce the charging expenses of IEVs (EVs with insufficient electricity). Besides, EVs and MCSs are selfish in terms of charging expenses and charging profits, respectively. In this article, we propose a Bayesian game based Bidding Scheme for Mobile Charging enabled Electric Vehicles (BBS-MCEV). In BBS-MCEV, each IEV first calculates the maximum charging price (MCP) according to the potential expense if charged by nearby FCSs, and then the optimal charging price (OCP) is determined by the Bayesian game model. Each MCS accepts the charging request with the largest charging profit. Extensive simulations and comparisons demonstrate the superior performance of our proposed BBS-MCEV, i.e., with the Bayesian game model, IEVs can rationally bid for the mobile charging services from MCSs, and thus BBS-MCEV can increase the charging profits of MCSs and reduce the charging expenses of IEVs effectively. Besides, a proper tradeoff between the charging profits of MCSs and the charging expenses of IEVs can be achieved.