模糊神经网络的离合器波形片轴滑磨控制

Sliding Wear Control of Clutch Wave Plate Shaft Based on Fuzzy Neural Network

离合器波形片轴滑磨控制受载荷条件影响,导致滑磨控制精度较差,因此提出一种新的基于模糊神经网络的离合器波形片轴滑磨控制方法。分析离合器波形片轴的结构,构建离合器总成动力学方程,获得离合器波形片轴的摩擦力矩。研究模糊神经网络五层结构,选择输入与输出变量,设定模糊规则,计算滑磨力矩,构建离合器有限元模型,确定热分析和静力分析模块约束及载荷条件。设定转速控制规则,完成滑磨控制。由仿真验证结果可知,所提方法能够精准计算滑磨力矩,有效控制滑磨温度与离合器接合速度,为保障离合器稳定运行奠定基础。

Due to the influence of load conditions,the control precision of clutch wavy disc shaft is poor.Therefore,a new control method of clutch wavy disc shaft based on fuzzy neural network is proposed.The structure of the corrugated disc shaft of the clutch is analyzed,the dynamic equation of the clutch assembly is constructed,and the friction torque of the corrugated disc shaft of the clutch is obtained.Thefive layer structure offuzzy neural network is studied.The input and output variables are selected,thefuzzy rules are set,the friction torque is calculated,the finite element model of clutch is constructed,and the constraints and load conditions of thermal analysis and static analysis module are determined.Set the speed control rules to complete the sliding control.The simulation results show that the proposed method can accurately calculate the friction torque,effectively control the friction temperature and clutch engagement speed,and lay the foundation for the stable operation of the clutch.