动车组应急蓄电池箱的多目标优化  

Multi⁃objective Optimization of Emergency Battery Box for Bullet Train

作　　者：李娅娜[1] 高佳威 LI Ya′na;GAO Jiawei(School of Locomotive and Rolling Stock Engineering,Dalian Jiaotong University,Dalian 116028,Liaoning,China)

机构地区：[1]大连交通大学机车车辆工程学院,辽宁大连116028

出　　处：《机械科学与技术》2024年第1期125-129,共5页Mechanical Science and Technology for Aerospace Engineering

基　　金：国家自然科学基金项目(52075066);辽宁省教育厅项目(LJKZ0497)。

摘　　要：针对动车组的应急蓄电池箱的安全问题和轻量化设计要求,综合多个优化目标对其进行优化分析。将主要部件的厚度作为设计变量,以应急蓄电池箱的总质量和和恶劣工况下的应力最小为优化目标,以其第1阶固有频率为约束函数,使用Box-Behnken设计方法获取样本数据。利用样本数据建立低阶多项式响应面模型,结合第三代非支配排序遗传算法(NSGA-Ⅲ)进行多目标优化。结果表明:相较于单一的响应面法或遗传算法,本文采用的响应面法与遗传算法结合的方式,使得优化后的参数更加合理,轻量化和安全性均得到了保障。Aiming at the safety problem and lightweight design requirements of train⁃set emergency battery box,the optimization analysis was carried out by integrating multiple optimization objectives.The thickness of the main components was taken as the design variables,the total mass of the emergency battery box and the minimum stress under harsh conditions were taken as the optimization objectives,and the first⁃order natural frequency was taken as the constraint function.The sample data were obtained by Box⁃Behnken design method.A low⁃order polynomial response surface model was established based on the sample data,and multi⁃objective optimization was carried out using the third⁃generation non⁃dominated sorting genetic algorithm(NSGA⁃Ⅲ).The results show that compared with the single response surface method or genetic algorithm,the combination of response surface method and genetic algorithm adopted in this paper makes the optimized parameters more reasonable,lightweight and safety are guaranteed.

关 键 词：响应面模型 NSGA-Ⅲ BOX-BEHNKEN设计 轻量化 安全性 

分 类 号：TG156[金属学及工艺—热处理]