基于RBF神经网络PID的摆销链式CVT速比控制策略研究

Research on speed ratio control strategy of chain CVT based on RBF neural network PID

通过对摆销链式CVT的工作原理进行分析,得出速比变化率对整车燃油经济性的影响规律,建立了基于RBF神经网络的PID控制器。运用Cruise与Simulink联合仿真,将建立的控制策略模型转换成DLL文件导入到Cruise中,分别在起步工况、制动工况、坡度工况和循环工况四种工况下进行仿真。仿真结果显示,通过对控制策略的调试,仿真结果得到的速比可以很好地跟随目标速比的变化,达到了RBF神经网络PID的调节要求,为摆销链式CVT的速比控制研究提供一定的理论依据。

Through the analysis of the working principle of chain CVT,the influence rule of speed ratio change rate on vehicle fuel economy was obtained,and the PID controller based on RBF neural network was established.Using Cruise and Simulink model,the established control strategy model was converted into DLL file and imported into Cruise,the simulation under starting condition,braking condition,slope condition and cycle condition was carried out.The simulation results show that through the debugging of the control strategy,the speed ratio obtained by the simulation can well follow the change of the target speed ratio,and meet the regulation requirements of RBF neural network PID,which provides a theoretical basis for the speed ratio control of chain CVT.