多目标优化在车门轻量化设计中的应用

Application of Multiobjective Optimization in Vehicle Door Lightweight

摘要:

为提高车门刚度并考虑轻量化的要求，提出以拼焊板车门下沉刚度和质量为优化目标，基于车门下沉刚度和窗框刚度两种工况，采用最优拉丁方试验设计方法进行样本数据设计,使用kriging模型拟合下沉刚度、窗框刚度、塑性变形量响应的近似模型，使用响应面模型拟合质量的近似模型.利用NSGAII遗传算法进行寻优，得到车门质量和下沉刚度的pareto优化解集，并对优化解进行验证，最终得到理想的优化结果.

Abstract:

In order to improve the door stiffness and simultaneously achieve the lightweight goal ,the sinking rigidity and mass of the tailedweld bank door were proposed as optimization objectives based on the door sinking stiffness conditions and window frame stiffness conditions, sampling points were obtained by using optimal latin hypercube, and the approximated system, including the door sinking stiffness, window frame stiffness and plastic deformation, was constructed by kriging model while the mass was fitted by response surface model. Nondominated sorting genetic algorithmII (NSGAII) genetic algorithm was used for multiobjective optimization, a pareto optimal solution set is gained, to verify this optimization solution, and eventually get the ideal optimization results.