9自由度主动悬架平顺性研究

基于汽车系统动力学理论，利用拉格朗日定理，推导设备-车-路耦合的9自由度主动悬架动力学方程，采用滤波白噪音作为左右车轮随机路面不平度激励，根据最优控制原理设计LQR控制器，建立主动悬架控制仿真模型.采用自适应粒子群算法优化加权系数Q，将主动悬架的设备加速度等性能参数均方根值与被动悬架进行对比分析.仿真结果表明:采用自适应粒子群算法优化LQR控制方法，能够显著改善车辆平顺性，保护车载设备可靠性. 

Study on Ride Comfort of Active Suspension with 9 Degrees of Freedom

Based on the theory of vehicle system dynamics and Lagrange''s theorem, the dynamics equation of the nine-degree freedom active suspension of the instrument-vehicle-road coupling was derived. White noise was used as the random road roughness excitation of the left and right wheels. LQR controller was designed according to the optimal control principle, and an active suspension control simulation model was established. An adaptive particle swarm algorithm was used to optimize the weighting coefficient Q, and the root mean square values of the equipment acceleration and other performance parameters of the active suspension were compared and analyzed with passive suspension. Simulation results show that the LQR controller, which is optimized by adaptive particle swarm optimization, can significantly improve the ride comfort and protect the reliability of on-board equipment.