重庆理工大学学报2024，Vol.38Issue(21)：10-17,8.DOI:10.3969/j.issn.1674-8425(z).2024.11.002
混合动力汽车多目标改进型粒子群算法优化研究
Research on multi-objective optimization of hybrid vehicles based on improved particle swarm algorithm
摘要
Abstract
To improve the economy,power and smoothness of hybrid electric vehicles,we take a parallel hybrid electric vehicle as the research object and employ the control strategy parameters and power system parameters as optimization variables,and the power battery charge balance as constraints to build a Multi-objective optimization model.During the optimization process,chaos operators and cosine strategies are introduced to improve the speed formula,inertia weight and learning factor of the particle swarm optimization algorithm.We propose an improved particle swarm optimization algorithm with simulation and optimization.Our results show while meeting the constraints,our algorithm improves the economy,ride comfort and power performance by 15.88％,11.71％and 3.51％respectively after optimization.Meanwhile,the efficiency distribution of the engine and motor operating points improve markedly.关键词
粒子群算法/多目标优化/混合动力汽车/Pareto最优解Key words
particle swarm optimization algorithm/multi-objective optimization/hybrid vehicles/Pareto optimal solution分类
交通工程引用本文复制引用
邓涛,马宝鹏,谭孟骑..混合动力汽车多目标改进型粒子群算法优化研究[J].重庆理工大学学报,2024,38(21):10-17,8.基金项目
国家自然科学基金项目(52275051) （52275051）
重庆市研究生联合培养基地建设项目(JDLHPYJD2022001) （JDLHPYJD2022001）
重庆交通大学自然科学类揭榜挂帅项目(XJ2023000701) （XJ2023000701）
重庆市研究生导师团队建设项目(JDDSTD2022007) （JDDSTD2022007）
