基于神经网络的车辆稳定性悬架阻尼控制仿真

Simulation of Suspension Damping Control Algorithm Based on Neural Network for Vehicle Stability Control

应用神经网络设计了车辆稳定性控制的悬架阻尼控制参数自整定算法。论述了基于神经网络的悬架阻尼控制算法的设计过程,搭建了软件在环仿真平台,针对典型工况进行了仿真研究与分析。结果表明:控制算法通过控制悬架阻尼,能有效抑制车轮载荷变化,实现控制整车横摆的目的,显著改善了车辆操纵稳定性。

Neural network was used to design suspension damping PID controllers whose parameters were optimized on line. The process of design of suspension damping control algorithm based on neural network was described, and a software-in-the-loop simulator was erected and simulations of typical conditions were made for research and analysis, The results show that the control algorithm can eliminate the variations of wheel load in order to control vehicle yaw rate by adjusting suspension damping. Handling and stability performance are improved evidently.