重庆理工大学学报2024，Vol.38Issue(15)：84-90,7.DOI:10.3969/j.issn.1674-8425(z).2024.08.009
基于适应度估计的动力电池冷却系统仿真优化加速方法
Simulation optimization and acceleration method of power battery cooling system based on fitness estimation
摘要
Abstract
In the process of simulation design optimization of power battery air cooling system,the technical route of"software simulation+evolution algorithm"is not efficient and thus has a low popularity.This paper proposes a method of simulation optimization and acceleration of power battery cooling system based on fitness estimation.In this method,the design schemes (individuals) in the population are divided into multiple subpopulations by AP clustering,and the fitness of representative individuals in the subpopulations is simulated by software simulation,and the fitness of non-representative individuals in the population is obtained by fitness estimation.Our experimental results show the algorithm effectively optimizes the design parameters of the power battery air cooling system and greatly cuts the optimization time of the system.When the objective function is set to the highest and average temperatures,the running time is reduced by 70.5％ compared with the traditional"Fluent simulation+genetic algorithm"technical route under the premise of achieving similar optimization results.关键词
动力电池风冷系统/参数优化/适应度估计/AP聚类Key words
power battery air cooling system/parameter optimization/fitness estimation/AP clustering algorithm分类
信息技术与安全科学引用本文复制引用
马占潮,张瑞乾,赵理,李玉琦,王震..基于适应度估计的动力电池冷却系统仿真优化加速方法[J].重庆理工大学学报,2024,38(15):84-90,7.基金项目
国家自然科学基金面上项目(52077007) （52077007）
