基于响应面模型的白车身多目标轻量化设计

基于MSC/NASTRAN软件平台建立了某多用途汽车（MPV）白车身有限元模型。首先，利用相对灵敏度分析方法选取了19个白车身零部件壁厚作为轻量化设计变量；然后，采用拉丁超立方试验方法和一阶响应面模型方法建立白车身质量、弯扭刚度、一阶弯扭模态的近似模型，模型的复相关系值R2都接近1.0，模型精度高；最后，以白车身质量最小和扭转刚度最大为优化目标函数，弯曲刚度和一阶弯扭模态为约束条件，采用非支配排序遗传算法对白车身进行多目标优化。优化结果表明，轻量化后的白车身弯扭刚度、一阶变扭模态变化均小于1.0%，且在不改变用材的前提下，实现白车身减重6.4kg。

Multi-object Lightweight Design of BIWs Based on Response Surface Model

The finite element model of BIW of a MPV type vehicle was established based on MSC/NASTRAN software platform. The thicknesses of 19 BIW panels were selected as lightweight design variables by using relative sensibility analysis method. Then, the metamodels of five different performance indexes were established using Latin hypercube sampling method and one order response surface model. The models have high accuracy which the multiple correlation coefficients R2 of all the models are close to 1.0. Finally, taking the minimum mass and maximum torsional stiffness as the objective function, and the bending stiffness and first-order bending and torsion modes as the restraints, a multi-objective lightweight optimization on the BIW was conducted by using NSGA-Ⅱ algorithm. The optimization results indicate that the changes of body performances after lightweight are less than 1.0%, and a weight reduction of 6.4kg is achieved.