Performance Optimization of Vehicle Handling and Stability Using Multiple Surrogate Models
Abstract
Handling and stability are key performances characteristics of vehicles. A vehicle with good handling performance can be controlled precisely by drivers and help avoid accidents. In this paper, the handling and stability optimization was conducted based on a multi-body dynamic vehicle model. Considering the large computational assumption numerical model calculation, surrogate modeling techniques were introduced in this study. The non-dominated sorting genetic algorithm version II (NSGA-II) method was applied in the optimization of each surrogate model. A comparison study on three different surrogate models was conducted to understand their performance in engineering problems. It showed that the simultaneous usage of different surrogate models was essential for obtaining the best possible design.