The utilization of every charging station varies greatly because the Electric Vehicle (EV) owners have great randomicity for choosing charging station, which causes the load imbalance of the whole power grid and affects the stability and security of the power grid. In view of the problem, minimum driving distance, minimum time and minimum deviation of time utilization rate and power utilization rate for charging station as optimization objectives, multi-objective optimal scheduling model of EVs for charging route is built. An improved Particle Swarm Optimization Algorithm based on Bacterial Chemotaxis (PSOBC) is proposed in order to solve the model. The simulation results show that the EV owners can purposefully choose charging stations according to the utilization of the charging stations in the area after adopting the proposed algorithm, which realizes the purpose of utilization equalization for charging stations. This work is supported by Industry-Academy-Research Cooperation Project of Jiangsu Province (No. BY2016026-01) and Natural Science Research Project in Universities of Jiangsu Province (No. 16KJB480006).