摘要
目前,对车门结构优化的研究多数没有考虑车门不确定性因素的影响。为了提高结构优化后车门性能的稳健性,将轧制差厚板应用于车门,同时考虑板料厚度和材料参数的波动对各约束响应稳健性的影响。结合拉丁超立方试验设计和径向基函数模型,采用蒙特卡罗模拟和改进型非支配遗传算法相结合的双循环优化策略,提出一种基于6σ稳健性的轧制差厚板车门多目标优化设计方法。研究结果表明,该方法在获得最优妥协解的同时,能提高设计变量的可靠性和目标函数的稳健性。
For car door structure optimization studies, most of them did not consider the car door uncertainty factors. In order to improve robustness of structure optimized car door,s performance, a new type manufacturing process of TRB was applied in car doors, and influences of sheet thicknesses and material performance parameter’s volatility on the robustness of each constraint were considered. Combined with Latin hypercube design and RBF model, using dual cycle optimization strategy of com-bining Monte Carlo simulation with improved non-dominated sorting genetic algorithm, a TRB car door lightweight design was proposed based on 6σ robustness. This method may obtain an optimal solution, and may improve reliability of design variables and robustness of objective function.
出处
《中国机械工程》
EI
CAS
CSCD
北大核心
2017年第8期996-1001,共6页
China Mechanical Engineering
基金
江苏省汽车工程重点实验室资助项目(1851120141)
关键词
车门
稳健性
轧制差厚板
蒙特卡罗模拟
轻量化
car door robustness
tailor rolled blank（TRB）
Monte Carlo simulation
lightweight
