摘要
针对我国汽车悬架控制系统智能化程度低,难以满足人们生产和生活的需求的问题,开发一种集合有CSO算法和PSO算法优点的混合算法:CSO-PSO算法。利用CSO-PSO算法进行三种不同路况下的半主动空气悬架的空气弹簧刚度优化,并将仿真结果与CSO,PSO算法分别进行比较。仿真结果表明,与CSO算法和PSO算法相比,CSO-PSO算法能够在保证安全性的前提下明显提高车辆乘坐舒适性。在三种仿真路况下,相对于被动悬架系统,CSO-PSO算法优化的半主动悬架系统的车身质心垂向加速度分别提高31.53%、35.14%、27.04%。
Aiming at the problem that China s automobile suspension control system is not intelligent enough and difficult to meet the needs of people s production and life,a hybrid algorithm,CSO-PSO algorithm,which combines the advantages of CSO algorithm and PSO algorithm is developed.The air spring stiffness optimization control of semi-active air suspension under three different road conditions is carried out using CSO-PSO algorithm,and the simulation results are compared with CSO algorithm and PSO algorithm respectively.The simulation results show that compared with the CSO algorithm and the PSO algorithm,the CSO-PSO algorithm can greatly improve the ride comfort of the vehicle under the premise of ensuring safety.Under the three simulated road conditions,the ride comfort of the semi-active suspension system controlled by CSO-PSO algorithm is increased by 31.53%、35.14%and 27.04%respectively,compared with the passive suspension system.
作者
袁春元
宋盘石
蔡锦康
王新彦
华周
Yuan Chunyuan;Song Panshi;Cai Jinkang;WanG Xinyan;Hua Zhou(College of Mechanical,Jiangsu University of Science and Technology,Zhenjiang,212000,China;PanoSim Technology Co.,Ltd.,Jiaxing,314000,China)
出处
《中国农机化学报》
北大核心
2020年第12期95-101,共7页
Journal of Chinese Agricultural Mechanization
基金
国家自然科学基金项目(51575249)。
关键词
半主动空气悬架
粒子群算法
MATLAB
空气弹簧
参数优化
semi-active air suspension
particle swarm optimization
MATLAB
air spring
parameter optimization