面向汽车外形空气动力学优化的代理模型方法

针对代理模型在汽车外形气动优化上的适应性研究较少的现状,运用不同数量样本点构建径向基函数(Radial Basis Function,RBF)模型、多项式模型和Kriging模型等3种常用代理模型.对比发现,在样本点相同的情况下,RBF模型的精度最高,最优解更好.在样本点增加的基础上,多项式和Kriging模型的精度提高,但计算量也大幅增加;多项式最优解更接近RBF模型的最优解,而Kriging模型最优解仍不理想.综合评估可知RBF模型更适用于汽车外气动优化.

Surrogate model method for aerodynamics optimization on automobile configuration

As to the fact that there is little study on the adaptability of surrogate model to automobile configuration aerodynamics optimization, three surrogate models in common use are built using different number of sample points, including Radial Basis Function(RBF) model, polynomial model and the Kriging model. The comparison indicates that the RBF model is with the best accuracy and good optimal solution in the case of the same sample points. When the sample points are increased, the accuracies of the polynomial model and the Kriging model are improved, but the calculation amount is increased significantly; the optimal solution of polynomial model is close to that of the RBF model, but the solution of Kriging model is not satisfactory. The comprehensive assessment shows that the RBF model is more suitable for the automobile aerodynamics configuration optimization.