摘要
以汽车行驶平顺性和乘坐舒适性为研究目标,为主动悬架系统提供了一种更可行的控制方法。基于1/4车四自由度主动悬架模型,分析了影响主动悬架动态特性的因素,并针对现存问题,把PID控制与神经网络相结合,提出一种单神经元PID控制策略,使神经元的连接权重对PID参数进行时时在线整定,以适应不同工况环境下悬架参数的变化。同时,以车身垂向加速度、悬架动挠度、轮胎垂向动载荷作为衡量指标进行仿真分析,并通过实验加以验证。结果显示,所用方法能够大幅提升主动悬架的动态性能,有效减小因路面激励所引起的车身颠簸,改善汽车乘坐舒适性和行驶平顺性。
With comfort and riding comfort as the goal,to provide a more feasible method for controlling the active suspension system. Based on a quarter car with four degrees of freedom active suspension model,analyzes the influencing factors of the active suspension dynamic character,and in the light of the existing problems,the combination of PID control and neural network,a single neuron PID control strategy and the neuron connection weights of PID parameters are always online tuning is proposed,in order to adapt to the change of the suspension parameters under different environmental conditions. At the same time,the vertical acceleration,the suspension dynamic deflection,the vertical load of the tire and the vertical load of the tire are simulated and analyzed by the experiments. The results show that the method can greatly improve the dynamic performance of the active suspension,effectively reduce the body bumps caused by pavement excitation,improve the ride comfort and ride comfort of the car.
出处
《机械设计与制造》
北大核心
2015年第10期249-252,共4页
Machinery Design & Manufacture
基金
"十二五"国家科技支撑计划(2014BAD06B00)
关键词
悬架
单神经元
PID控制
实验
Suspension
Single neuron
PID control
Experiment
