DOI: 10.11908/j.issn.0253-374x.19404

作者:

作者单位: 1.同济大学 汽车学院，上海 201804;2.科力远混合动力技术有限公司，上海 201501


作者简介: 耿文冉（1986—)，女，博士生，主要研究方向为功率分流式混合动力系统结构优化及能量管理策略。E-mail: gengwenran@126.com


通讯作者: 楼狄明（1963—)，男，教授，博士生导师，工学博士，主要研究方向为混合动力技术、车辆排放控制技术、发动机先进燃烧技术等。 E-mail: loudiming@tongji.edu.cn

中图分类号: U469


基金项目: 国家重点研发计划（2017YFE0102800）




Multi-objective Energy Management Strategy for Hybrid Electric Vehicle Based on Particle Swarm Optimization
Author:

Affiliation: 1.School of Automotive Studies, Tongji University, Shanghai 201804, China;2.Corun Hybrid Technology Co., Ltd., Shanghai 201501, China


Fund Project:




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摘要:为了同时实现降低整车能耗和控制电池电量的能量管理目标，针对某功率分流式混合动力汽车，提出了基于粒子群优化(PSO)的多目标能量管理策略。该策略采用双层结构，内层采用考虑模式切换的等效燃油消耗最少策略(ECMS)对工作模式和工作点进行优化，实现降低整车能耗的目标；外层采用PSO对等效因子进行迭代优化，实现电池电量的控制目标。通过基于实车控制策略的整车仿真模型对优化效果进行了验证，结果表明，PSO与ECMS相结合的能量管理策略可实现降低整车能耗与控制电池电量的双重目标。



Abstract:In order to reduce vehicle energy consumption and control battery state of charge(SOC) at the same time, a multi-objective energy management strategy based on particle swarm optimization (PSO) was proposed for a power-split HEV. The proposed strategy adopted a two-layer structure. The inner layer used the equivalent consumption minimization strategy (ECMS) that considered mode switching to optimize the operation mode and operating point, so as to achieve the goal of energy saving. The outer layer used PSO to optimize the equivalent factor iteratively to achieve the control of battery power. Then, a vehicle simulation model based on the real vehicle control strategy was used to verify the optimization effect. Simulation results show that, the energy management strategy combined with PSO and ECMS can achieve the dual goals of reducing vehicle energy consumption and controlling battery SOC.





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