A chaotic particle swarm optimization algorithm for solving optimal power system problem of electric vehicle

Abstract

Transportation of electrification has become a hot issue in recent decades and the large-scale deployment of electric vehicles has yet to be actualized. This article proposes a powertrain parameter optimization design approach based on chaotic particle swarm optimization algorithm. To improve the driving and economy performance of pure electric vehicles, chaotic particle swarm optimization algorithm is adopted in this study to optimize principal parameters of vehicle power system. Vehicle dynamic performance simulations were carried out in the Cruise software, and the simulation results before and after optimization were compared. Simulation results show that optimized vehicles by chaotic particle swarm optimization can meet the expected dynamic performance and the driving range has been greatly improved. Meanwhile, it is also viable that the parameters of the optimal objective function can achieve the purpose of balancing the driving performance and economic performance, which provides a reference for the development of vehicle dynamic performance.