基于Taguchi与TOPSIS-熵的车门多目标离散稳健优化研究

摘要

车身轻量化已经成为当前研究的重要方向,而车门作为汽车车身的一个相对独立的部件,如何在保证性能要求的基础上实现其轻量化是当前研究的热点.为实现车门轻量化,并保证其刚度、模态及耐撞性等性能,同时提高设计的稳健性,提出了一种基于连续Taguchi方法和TOPSIS-熵的多目标离散稳健优化算法;该方法充分利用了试验数据的决策信息,使优化效率大大提高.采用提出的算法对国内某款汽车前门结构进行优化的结果表明,不仅能满足刚度和模态要求,车门质量下降了28.44 %,柱碰工况所吸收的能量增加了3.07 %,同时提高了车门系统的稳健性,在工程实际中,具有非常强的实用性.%The door system is a relatively independent part in the vehicle body.Its mass,stiffness,modal and crashworthiness have a significant effect on vehicle performance.To reduce the mass of the vehicle door and ensure the stiffness,modal and crashwor-thiness performance,a novel multi-objective discrete robust optimization algorithm which is achieved by coupling successive Tagu-chi method with TOPSIS entropy-technique for order preference by similarity to ideal solution is proposed to optimize the struc-tures of automobile door involving disturbance factors. This algorithm makes full use of the decision information of the test date to improve the optimization efficiency.It can avoid the problem in which weight is not objective in traditional method.The result of the example shows that the method can not only ensure the stiffness and the modal performance,but also can make the weight re-duce by 28.44 % as well as the absorbed energy in the crash increase by 3.07 %.In addition,the robustness of the door system has been improved.This method has high engineering application value.