基于SOA-LQR控制的电控空气悬架系统  

Electronically Controlled Air Suspension System Based on SOA-LQR Control

作　　者：郑爽 范例[1] Zheng Shuang;Fan Li(College of Mechanical Engineering,Anhui University of Science and Technology,Huainan 232001,China)

机构地区：[1]安徽理工大学机械工程学院,安徽淮南232001

出　　处：《湖北汽车工业学院学报》2023年第2期7-12,共6页Journal of Hubei University Of Automotive Technology

基　　金：安徽理工大学青年教师科学研究基金(QN2019117)。

摘　　要：为研究电控空气悬架系统(ECAS)的控制策略,基于MATLAB/Simulink平台搭建了空气悬架模型,以白噪声路面作为系统输入,采用LQR最优控制器实现悬架力的输出,并以人群搜索算法作为控制器优化方式,完成对空气悬架LQR控制器中所包含的主要指标权重数据优化,仿真结果表明,优化后的LQR控制系统对于ECAS的性能提升具有较好效果,其中簧上质量垂直加速度、动挠度瞬态响应峰值相较无控制状态分别减小了45.84%和39.07%,均方根值则分别减小了54.98%和35.4%,整车平顺性得到较大改善。In order to study the control strategy of the electronically controlled air suspension system(ECAS),an air suspension model was built based on the MATLAB/Simulink platform.The white noise road surface was used as the system input,and the LQR optimal controller was used to output the sus‐pension force.The seeker optimization algorithm(SOA)was used to optimize the controller and the main index weight data contained in the air suspension LQR controller.The simulation results show that the optimized LQR control system can better improve the performance of ECAS.Compared with those under the uncontrolled state,the vertical acceleration of the sprung mass and the transient response peak of dynamic deflection are reduced by 45.84%and 39.07%,respectively.In addition,the rootmean-square values are reduced by 54.98%and 35.4%,respectively,and the vehicle’s ride comfort is greatly improved.

关 键 词：电控空气悬架 LQR 人群搜索算法 平顺性 

分 类 号：U461.6[机械工程—车辆工程]