车辆EPS模糊神经网络控制研究

The Fuzzy Neural Network Control Research on Vehicle with EPS

在二自由度车辆转向和EPS动力学模型建立的基础上,设计了EPS模糊神经网络控制系统结构及其控制策略。对不同转向盘转角输入工况进行仿真计算。结果表明,与传统的机械式转向系统相比,有助力时车辆的横摆角速度峰值和标准差分别减少了5.2%和11.2%;车身侧偏角的峰值和标准差分别减少了29.2%和28.7%,结果证明了模型的正确性和控制策略的有效性。

EPS control system based on fuzzy neural network control theory and its control strategy were disigned on the basis of EPS and vehicle two degrees of freedom dynamic model construction. Simulation was carried out on different steering wheel angle input conditions. The simulation results show that, the vehicle yaw rate peak and standard deviation are reduced by 5.2% and 11.2% in compared with the traditional mechanical steering system, peak and standard deviation of the angle of the vehicle body side are reduced by 29. 2% and 28.7%. the validity of the model and the effectiveness of the control strategy are proved by the results.