耐撞性, Kriging模型, 最小二乘响应面模型, 径向基函数模型, 拉丁超立方, 自适应模拟退火算法

The thicknesses of vehicle front parts were defined as variables, and 100 points of vehicle front crash finite element models were sampled by the Latin hypercube design of experimental method. The Kriging model, LSR model and RBF model were then applied to construct the approximate models of the weight of front structure, the maximal acceleration of B pillar and the maximal absorbed energy of front structure according to the FEM simulation results. In the optimization of maximal acceleration of B pillar, the weight of front structure, the maximal absorbed energy of front structure and the thickness of vehicle front parts were constrained. Then, an ASA algorithm and searching the best result in a large number of samples in three spaces were adopted to minimum the maximal acceleration of B pillar and find an optimal thickness of the front parts. The study shows that the precision and efficiency of this method is good and can meet the crashworthiness engineering requirements.

crashworthiness, Kriging model, least squares regression(LSR) model, radial basis function(RBF) model, Latin hypercube, adaptive simulated annealing(ASA)