插电式混合动力汽车能量管理策略多目标优化

能量管理策略与插电式混合动力汽车(plug-in hybrid electric vehicles,PHEV)的燃油消耗和尾气排放密切相关.在开发的PHEV能量管理策略基础上,建立整车仿真模型.利用自适应惯性因子对基本粒子群算法进行改进.为克服单一优化算法的固有缺陷,将改进粒子群算法和遗传算法组成混合优化算法,并将该混合算法应用于PHEV能量管理策略的多目标优化.优化结果表明,该算法能有效跳出局部最优,其寻优能力明显高于基本粒子群算法和遗传算法,优化后的PHEV油耗和尾气排放相对于优化前减少近30%.

Multi objective Optimization of Energy Management Strategy of Plug in Hybrid Electric Vehicle

Energy management strategy is related to fuel consumption and exhaust emissions of Plug-in Hybrid Electric Vehicle (PHEV). Vehicle simulation model is established on the base of energy management strategy developed in this paper. In order to overcome the inherent defects in single optimization algorithm, Improved Particle Swarm Algorithm (IPSO), obtained from initial PSO which using adaptive inertial factor, and Genetic Algorithm (GA) constitute hybrid optimization algorithm which is applied in the multi-optimization of energy management strategy of PHEV. Optimization results show that the hybrid optimization algorithm can avoid falling into local optimum and is much better than initial PSO and GA. The optimized fuel consumption and exhaust emissions are reduced relatively by approximately 30%.