doi:10.16186/j.cnki.1673-9787.2020.2.10

Received:2019/04/26

Revised:2019/05/19

Published:2020/03/15

Research on semi-active fuzzy-PI control suspension of semi-completevehicle based on particle swarm optimization

CHEN Guoqiang1, LYU Shaobin1, LI Gensheng2, DAI Jun1, YANG Zhifei1

1.School of Mechanical and Power Engineering， Henan Polytechnic University， Jiaozuo  454000 ， Henan， China;2.School of Vehicle and Transportation Engineering， Henan University ofScience and Technology， Luoyang  471003 ， Henan， China

Abstract:Aiming at the complex mechanical properties of the vehicle suspension under different road conditions ，the numerical analysis method was proposed to study the performance characteristics of the semi-active suspension of the semi-complete vehicle. According to the mechanical principle of the semi-complete semi-active suspension， the semi-active dynamics mathematical model of the semi-complete vehicle was established. The fuzzy-PI control suspension system was obtained by using two fuzzy-PI controllers to respectively control the front and rear wheels of the vehicle. The fuzzy-PI control suspension system was obtained by using particle swarm optimization. The variation law and root mean square values of the acceleration of the vehicle body centroid ，the acceleration of the vehicle body pitch angle， the deformation of the front and rear wheels， and the dynamic deflection of the front and rear suspension were obtained. The influence of the suspension performance parameters on vehicle performance and the intrinsic relationship between performance parameters were analyzed. The reliabilities of the two PI control suspensions were analyzed. The results showed that the performances of the two types of PI control suspensions were greatly improved compared with the passive suspension， and the comprehensive performance of the fuzzy-PI control suspension based on particle swarm optimization was the best. The two types of PI control suspensions had good reliability when the vehicle ran on the different roads.

Key words:suspension performance;semi-active suspension;particle swarm optimization;double fuzzy-PI con;

基于粒子群优化的半整车半主动模糊PI_控制悬架研究_陈国强.pdf