重庆理工大学学报2024，Vol.38Issue(15)：74-83,10.DOI:10.3969/j.issn.1674-8425(z).2024.08.008
基于工况识别的P2.5构型PHEV能量管理策略
Research on energy management strategy of PHEV with P2.5 configuration based on working condition identification
摘要
Abstract
Appropriate energy management strategy effectively improves the range of hybrid vehicles.This paper investigates the energy management strategy for condition identification of dual power source plug-in hybrid electric vehicle (PHEV) with P2.5 configuration by constructing the whole vehicle model through Matlab/Simulink.Nineteen domestic and international typical cycling conditions are selected and classified into three categories by hierarchical cluster analysis according to the characteristics of the conditions,and a support vector machine condition identification model is built and optimized by using the whale algorithm.Our simulation results show the identification accuracy of the optimized condition identification model rises to 97.905％ from 76.259％ recorded with the pre-optimization model,up by 21.646％.Combined with the online working condition recognition model,the power allocation results of the dynamic planning energy management strategy under different working condition categories are learned through neural networks,and the offline learning results are applied to the online control to formulate the energy management strategy based on working condition recognition.Our simulation results show compared with the Charge Depleting-Charge Sustaining (CD-CS) strategy,tthe energy management strategy based on operating condition recognition improve its economy by 7.62％.关键词
插电式混合动力汽车/能量管理策略/工况识别/动态规划/神经网络Key words
plug-in hybrid vehicles/energy management strategies/condition recognition/dynamic planning/neural networks分类
交通工程引用本文复制引用
罗勇,李豪,翁勇永,李莉莎,李小凡,孙强..基于工况识别的P2.5构型PHEV能量管理策略[J].重庆理工大学学报,2024,38(15):74-83,10.基金项目
重庆市技术创新与应用发展重大专项(CSTB2022TIAD-STX0005) （CSTB2022TIAD-STX0005）
重庆市教委科学技术研究项目(KJQN202201125) （KJQN202201125）
重庆理工大学重大科研项目(2022TBZ003) （2022TBZ003）
