西华大学学报（自然科学版）2024，Vol.43Issue(3)：54-63,10.DOI:10.12198/j.issn.1673-159X.4834
基于工况识别的PHEV能量管理策略
Energy Management Strategy for PHEV Based on Condition Recognition
摘要
Abstract
As for the disadvantage of poor adaptability of equivalent fuel consumption minimum strategy (ECMS) under different working conditions, the energy management strategy of variable equivalent factor ECMS based on condition recognition algorithm is designed to improve fuel economy of parallel hybrid electric vehicles(PHEV). The vehicle equivalent fuel consumption is optimized as the optimization objective. Three typical working conditions were selected to establish the SVM classification model, the sample features were selected by recursive feature elimination method, and the whale algorithm was used to optimize the parameters of the SVM. The simulated annealing algorithm was used to solve the ECMS equivalent factors of the three types of working conditions for offline global optimal solution, and were stored in the equivalent factor library respectively. The target optimized working conditions were identified by the trained support vector machine classifier. Different types of working conditions were treated with different equivalent factors for torque distribution. Compared with the logic threshold energy management strategy, the variable equivalent factor ECMS energy management strategy based on the condition recognition algorithm reduced the variation of State of charge (SOC) by 8.67%, and the fuel saving rate by 13.11%.Compared with the ECMS strategy before optimization, the SOC variation of battery was reduced by 3.47%,and the fuel saving rate was about 6.63%.The variable equivalent factor ECMS energy management strategy based on the driving condition recognition algorithm can effectively reduce the fuel consumption and improve the economy of the PHEV.关键词
并联混合动力汽车/能量管理策略/工况识别/鲸鱼优化算法/支持向量机/递归特征消除/等效燃油消耗最小Key words
parallel hybrid electric vehicle/energy management strategy/working condition identification/whale optimization algorithm/support vector machine/recursive feature elimination/minimum equivalent fuel consumption分类
交通工程引用本文复制引用
张代庆,牛礼民,汪恒,张义奇..基于工况识别的PHEV能量管理策略[J].西华大学学报（自然科学版）,2024,43(3):54-63,10.基金项目
先进数控和伺服驱动技术安徽省高校重点实验室开放基金资助项目(XJSK202104) （XJSK202104）
电气传动与控制安徽省重点实验室开放基金资助项目(DQKJ202204). （DQKJ202204）
