摘要
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.
出处
《系统仿真学报》
EI
CAS
CSCD
北大核心
2007年第16期3813-3815,3837,共4页
Journal of System Simulation
基金
长春市振兴老工业基地科技攻关及市
院合作计划资助项目(2004175)
关键词
车辆工程
悬架阻尼
神经网络
仿真
操纵稳定性
vehicle engineering
suspension damping
neural network
simulation
handling and stability
