摘要
选择汽车正面碰撞耐撞性为优化目标,结合最优拉丁超立方样本点设计、RBF模型以及NSGA-Ⅱ多目标优化对设计变量进行优化。为了加快目标值收敛速度并寻求可能存在的初始设计域之外的最优解,引入空间收缩回归法在迭代过程中对设计域进行动态更新。优化迭代过程最终收敛到一组最优解,使得在未增加车身总质量的条件下提升了车身正面碰撞耐撞性。通过与有限元模型计算结果进行对比分析,验证了该方法具有收敛速度快和寻优精度高的特点。
The frontal crashworthiness of a vehicle was chosen to be optimized herein.Opt LHD method,RBF model and NSGA-Ⅱ multi-objective optimization method were combined to optimize design variables.To accelerate the convergences of objectives in the process and seek latent solutions out of the initial design space,the shrinking space regression method was introduced to refresh the design region dynamically.The convergence conditions were finally met after several rounds of iteration.An optimal solution was reached,which promoted the frontal crashworthiness shapely without any mass increased.The fast convergence and high accuracy of this method was proved by the comparison between predicted and FEA results.
出处
《中国机械工程》
CAS
CSCD
北大核心
2015年第17期2406-2413,共8页
China Mechanical Engineering
基金
中央高校基本科研业务费专项基金资助项目(2013-IV-118)
上汽通用五菱汽车股份有限公司校企合作项目(S-C08-01W01-P04-OR02)
关键词
空间收缩回归
设计域
正面碰撞
耐撞性
shrinking space regression
design space
frontal impact
crashworthiness
