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基于模糊PID算法的磁流变悬架系统的控制仿真研究

Research on Control Simulation of Magnetorheological Suspension System Based on Fuzzy PID Algorithm
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摘要 为了改善车辆的行驶平顺性,选择车速为30 m/s、路面激励为C级的工况条件,对被动控制、模糊控制和模糊PID控制的磁流变悬架系统进行MATLAB仿真,并选取车身垂向加速度、悬架动挠度和轮胎动载荷作为行驶平顺性的评价指标。结果表明:与被动控制的悬架系统比较,模糊PID控制与模糊控制的磁流变悬架系统的垂向加速度均方根值分别为28.02%、9.40%,峰值改善率分别为24.68%、2.49%;模糊PID控制与模糊控制的磁流变悬架系统的悬架动挠度均方根值分别为20%、10%,峰值改善率分别为13.58%、13.58%;模糊PID控制与模糊控制的磁流变悬架系统的轮胎动载荷均方根值分别为0.18%、0.003%,峰值改善率分别为3.79%、2.64%。 In order to improve the ride comfort of vehicles,under the working conditions of 30 m/s speed and C-level road excitation,the passive control,fuzzy control and fuzzy PID control of magnetorheological suspension system are simulated by MATLAB,and the vertical acceleration of vehicle body,dynamic deflection of suspension and dynamic load of tires are selected as the evaluation indexes of ride comfort.The results show that compared with the passive suspension system,the root mean square values of vertical acceleration of fuzzy PID control and fuzzy control magnetorheological suspension system are 28.02%and 9.40%respectively,and the peak improvement rates are 24.68%and 2.49%respectively.The root mean square values of suspension dynamic deflection of fuzzy PID control and fuzzy control magnetorheological suspension system are 20%and 10%respectively,and the peak improvement rates are 13.58%and 13.58%respectively.The root mean square values of tire dynamic load of fuzzy PID control and fuzzy control magnetorheological suspension system are 0.18%and 0.003%respectively,and the peak improvement rates are 3.79%and 2.64%respectively.
作者 熊新 潘则宇 XIONG Xin;PAN Zeyu(School of Automotive Engineering,Yancheng Institute of Technology,Yancheng Jiangsu 224051,China)
出处 《盐城工学院学报(自然科学版)》 CAS 2023年第4期48-56,共9页 Journal of Yancheng Institute of Technology:Natural Science Edition
关键词 磁流变悬架 模糊PID控制 垂向加速度 动挠度 动载荷 magnetorheological suspension fuzzy PID control vertical acceleration dynamic deflection dynamic load
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