现代制造工程Issue(1)：63-68,6.DOI:10.16731/j.cnki.1671-3133.2018.01.013
基于改进粒子群算法的车辆被动悬架优化与仿真研究
Optimization and simulation of vehicle passive suspension based on improved particle swarm optimization algorithm
摘要
Abstract
Aiming at the problem of white noise,the vehicle passive suspension model with four degrees of freedom is created,and the dynamic equation of the vehicle's vertical direction is derived.The hybrid objective function is constructed,and the improved particle swarm optimization algorithm is used to optimize the parameters of the passive suspension model of four degrees of free-dom quarter vehicle.The vehicle passive suspension system simulation model was established,and the dynamic simulation was carried out by Matlab/Simulink software at different speed,and the simulation results are compared with those before optimiza-tion.The simulation results show that the root mean square after optimization of vehicle passive vertical suspension driver head ac-celeration,sprung vertical stroke and unsprung vertical displacement of the maximum value were reduced by 51 %,45.4 % and 40.7 %,and the peak vibration of vehicle vertical direction was also reduced.Improved particle swarm optimization algorithm is used to optimize the vehicle passive suspension system,which can improve the stability of vehicle driving and improve the ride comfort of the vehicle.关键词
改进粒子群算法/车辆被动悬架/优化/仿真Key words
improved particle swarm optimization algorithm/vehicle passive suspension/optimization/simulation分类
交通工程引用本文复制引用
安宗权,王匀..基于改进粒子群算法的车辆被动悬架优化与仿真研究[J].现代制造工程,2018,(1):63-68,6.基金项目
国家自然科学基金项目(50975126) （50975126）
安徽省教育厅自然科学研究重点项目(KJ2016A753) （KJ2016A753）
江苏省重点研发计划项目(SBE2016000575) （SBE2016000575）
