机械科学与技术2024，Vol.43Issue(5)：819-831,13.DOI:10.13433/j.cnki.1003-8728.20220283
Pareto排序遗传算法及响应面优化在纯电车电池壳体参数设计的工程应用
Engineering Application of Pareto Sorting Genetic Algorithm in Parameter Design of Battery Case of Pure Electric Car
摘要
Abstract
To solve the problems of massive and stress concentration of ternary lithium battery case.The parameters after the variable density topology optimization were sampled using the Latin hypercube method,and the Pareto ranking multi-objective genetic algorithm was utilized to select stresses,etc.as the objective function for iterative calculation.The paper used Kriging space interpolation to obtain each response profile and a preliminary predicted optimization scheme.Based on the above results,a 62-group response surface mathematical model was established using Design-Expert,and the calculated Pareto optimum was 70%,with the p-value≤0.000 1.This proves the accuracy of the response surface model,and the performance of the optimized structure after simulation has been improved in all aspects compared to the original model,with better reliability.关键词
纯电动汽车/多目标遗传算法/响应面优化Key words
pure electric vehicle/multi-objective genetic algorithm/response surface optimization分类
交通工程引用本文复制引用
高媛媛,刘娜,刘鹏,王成诺..Pareto排序遗传算法及响应面优化在纯电车电池壳体参数设计的工程应用[J].机械科学与技术,2024,43(5):819-831,13.基金项目
山东省高等教育科技计划(J18KA006)与交通运输行业车辆测试、诊断与维护技术关键实验室开放基金项目(JTZL2004) （J18KA006）
