An Adaptive Metamodel-Based Optimization Approach for Vehicle Suspension System Design

Abstract

The performance index of a suspension system is a function of the maximum and minimum values over the parameter interval. Thus metamodel-based techniques can be used for designing suspension system hardpoints locations. In this study, an adaptive metamodel-based optimization approach is used to find the proper locations of the hardpoints, with the objectives considering the kinematic performance of the suspension. The adaptive optimization method helps to find the optimum locations of the hardpoints efficiently as it may be unachievable through manually adjusting. For each iteration in the process of adaptive optimization, prediction uncertainty is considered and the multiobjective optimization method is applied to optimize all the performance indexes simultaneously. It is shown that the proposed optimization method is effective while being applied in the kinematic performance optimization of a McPherson suspension system.