摘要
考虑到空气弹簧的非线性特性,建立了2自由度车辆空气悬架系统的振动模型。为了提高车辆行驶平顺性和乘坐舒适性,设计将粒子群优化(Particle Swarm Optimization,PSO)算法与PID控制策略相结合后应用于车辆空气悬架系统控制,并在Matlab/Simulink环境下,对不同车速和行驶路况下的车辆空气悬架进行了仿真分析。仿真结果表明:与传统的PID控制比较,基于粒子群优化的PID控制器使得车辆空气悬架系统的车身垂向加速度(BA),悬架动行程(SWS)和轮胎动位移(DTD)的均方根值都有所减少,改善了车辆的平顺性和操纵稳定性。
Considering the nonlinear characteristics of air spring, a vibration model of two degree of freedom vehicle air suspension system is built. In order to improve the comfort of vehicle riding, we combine Particle Swarm Optimization algorithm with PID control strategy and use it to vehicle air suspension system control, simulation analysis with different driving conditions and speed of the vehicle air suspension is made in Matlab/Simulink environment. The simulation results illustrate that, compared with the traditional PID control, the proposed algorithm can reduce the root mean square of BA, SWS and DTD, the riding comfort and handling stability of vehicle air suspension are improved.
出处
《计算机仿真》
CSCD
北大核心
2015年第1期197-201,共5页
Computer Simulation
基金
福建省产学研重大项目资助(2012H6016)
福建省自然科学基金计划资助项目(2011J01321)
关键词
粒子群优化算法
空气悬架
仿真分析
Particle swarm optimization algorithm
Air suspension
Simulation analysis