应用磁流变阻尼器的车辆半主动座椅悬架系统性能研究

Research on Performance of Vehicle Semi-Active Seat Suspension System Applied Magnetorheological Damper

为寻求车辆半主动座椅悬架控制策略使其达到较好的减振效果,对应用磁流变液阻尼器的汽车座椅悬架进行了建模研究。利用BP神经网络的自适应学习功能,通过采集偏差信号对传统PID控制策略的控制参数进行实时在线整合,使得座椅悬架具有更强的适应性和更好的减振效果。在MATLAB/Simulink工具箱建立了人-座椅-车七自由度的系统仿真模型,对比PID控制策略以及被动模型,验证了该控制方法的可行性与有效性,能够减小驾驶员在车辆行驶过程中,由路面经座椅悬架传递至驾驶员头部的振动的幅值和加速度。

To seek the control strategy of semi-active vehicle seat suspension to achieve a better vibration reduction effect,the modeling study of vehicle seat suspension using magnetorheological fluid damper was carried out. The self-adaptive learning function of BP neural network is applied to integrate parameters of traditional PID control strategy in real time by collecting deviation signals,so that the seat suspension will have a better adaptability and vibration damping performance. The simulation model of seven degrees of freedom of human-seat-vehicle was established by MATLAB/Simulink toolbox and comparing the PID control strategy and the passive model,the feasibility and effectiveness of the control method are verified,which can reduce the amplitude and acceleration of vibration transmitted from the road surface to the driver′s head through the seat suspension during the driving process.