基于多学科优化设计的车门轻量化研究

采用均匀拉丁方试验设计和利用移动最小二乘法建立了车门模态、刚度、强度和侧柱碰的多学科近似响应面模型,将关键部件的厚度作为设计变量,以各项结构性能为约束,以车门重量最小为优化目标,最后利用自适应响应面法进行多学科优化设计并得到了较好的优化结果,优化结果进行了工程解读及有限元验证。最终的优化结果显示各项结构性能满足要求而且分布更加均衡,同时实现了较好的轻量化效果,优化方案具有较强的工程实用性。     

A new approach of intelligent design and optimization for shell nosing

Preform design for shell nosing product without machining the inner surface after forming is an experience-extensive work. Generally, the initial design needs to be modified and simulated consequently to get proper preform and nosing die, and the iterative process is time consuming. This paper puts forward a new approach, in which the suitable initial design can be obtained by knowledge-based intelligent technology and the optimal design can be acquired by finite element method (FEM) based geometrical modification. With the CAX object model as the bridge of CAD and CAE, the CAD model with simulation knowledge can be transferred into CAE automatically, and the CAE result can be automatically utilized as well. Based on the comparison between the simulated shape and the desired shape, the dissatisfactory area will be modified. A new simulation and modification process will be carried out based on the modified design. The process is repeated iteratively to get the optimal design. This approach utilizes the commercial CAD and CAE software, without the need of complex back-forward FEM procedures. Based on the new approach, an in-home intelligent shell nosing design and optimization system is developed, and a case study proves that this system can reach a reasonable design efficiently.