Performance Optimization of Vehicle Handling and Stability Using Multiple Surrogate Models
Performance Optimization of Vehicle Handling and Stability Using Multiple Surrogate Models
复制标题
DOI：
10.1520/jte20150161
复制
发表时间：
2016-11
影响因子：
1.2
通讯作者：
T. Shi;Shuming Chen;Dengfeng Wang;J. Chen
中科院分区：
文献类型：
--
作者：
T. Shi;Shuming Chen;Dengfeng Wang;J. Chen
操控性和稳定性是车辆的关键性能特征。操控性能好的车辆可以被驾驶员精确控制，有助于避免事故的发生。本文基于多体车辆动力学模型进行了操纵稳定性优化。考虑到数值模型计算的计算假设较大，本研究引入了替代建模技术。采用非支配排序遗传算法版本II （NSGA-II）方法对各代理模型进行优化。对三种不同的代理模型进行了比较研究，以了解它们在工程问题中的性能。这表明，同时使用不同的代理模型是获得最佳设计的必要条件。
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.