基于多目标遗传算法的混合动力汽车能量管理优化

混合动力技术是实现汽车节能减排的有效途径。本文P2混合动力汽车为研究对象，考虑SOC状态分别为高、中、低三种不同的电量模式时，设计不同的能量管理策略，以实现混合动力汽车节能减排的同时维持SOC的平衡的目的。该策略在基于规则的基础上采用Isight软件中的多目标遗传算法对门限值进行优化，以提高能量管理策略中门限值的可靠性和有效性。仿真结果表明该能量管理策略对降低车辆油耗的效果显著，并且能很好的维持电池SOC的平衡。

Optimization of HEV Energy Management Based on Multi Objective Genetic Algorithm

Hybrid technology is an effective way to achieve energy saving and emission reduction. This paper takes P2 hybrid electric vehicle as the research object, and designs different energy management strategies when SOC state is high, medium and low respectively, so as to achieve the purpose of energy saving and emission reduction of hybrid electric vehicle while maintaining the balance of SOC. In order to improve the reliability and effectiveness of the threshold value in the energy management strategy, the multi-objective genetic algorithm in Isight software is used to optimize the threshold value on the basis of rules. The simulation results show that the energy management strategy has a significant effect on reducing vehicle fuel consumption, and can maintain a good balance of battery SOC.