多目标遗传算法在整车轻量化优化设计中的应用研究  

Design Optimization on Lightweight of Full Vehicle Based on Multi-objective Genetic Algorithm

作　　者：张勇[1] 李光耀[1] 王建华[1] 

机构地区：[1]湖南大学汽车车身先进设计制造国家重点试验室,长沙41008

出　　处：《中国机械工程》2009年第4期500-503,共4页China Mechanical Engineering

基　　金：国家自然科学基金资助重点项目(60635020);长江学者和创新团队发展计划资助

摘　　要：采用D-最优试验设计方法对汽车前部关键吸能部件的材料和板料厚度进行多参数空间的样本数据设计;为提高计算效率,将能够代表整车正面碰撞过程的高精度多参数近似模型引入到整车轻量化优化设计中,并利用多目标遗传算法对近似模型进行优化,使得车身前部吸能部件的板料厚度和材料得到合理配置,同时也使得整车质量和B柱加速度尽可能最小。在车辆安全性满足CMVDR294安全法规的同时,也在一定程度上减小了整车的质量。Sampling data of thickness and material of automobile＇s body front key absorbing energy parts were obtained by the D-- optimal experimental design method. Meantime, in order to improve computing efficiency, high accuracy meta--model that can substitute the front impact process was introduced to optimize design of automobile lightweight,then,the recta--model was optimized by using the multi--objective genetic algorithm. As a result,thickness and material of automobile＇s body front key absorbing energy parts achieve reasonable configuration, meanwhile, automobile＇s weight and B pillar＇s acceleration achieve optimization as far as possible. It lightens the weight of full vehicle to meet the requirements of regulation CMVDR294.

关 键 词：轻量化 D-最优试验设计 响应面近似模型 多目标遗传算法 

分 类 号：TG302[金属学及工艺—金属压力加工]