Optimization Control of CVT Clutch Engagement Based on MPC

Abstract

As an important part of continuously variable transmission (CVT) vehicle power transmission system, drive, neutral and reverse (DNR) wet clutch has the function of transmitting or interrupting vehicle power. However, due to the complex and variable working conditions of the clutch, it is difficult to achieve precise control of the clutch by the traditional control strategy. To solve this problem, a clutch control optimization algorithm based on model predictive control (MPC) is proposed. In order to identify and track the driver's launching intentions, a driver's launching intentions recognition system based on fuzzy neural network (FNN) is designed. The impact degree and friction work are taken as the evaluation standard of clutch control. The clutch controller is designed by using MPC control strategy, and the control effect is compared with the adaptive fuzzy neural network (AFNN) strategy. Finally, the validity of the control strategy is verified by simulation model and vehicle test. The results show that compared with the AFNN control strategy, the MPC control strategy can effectively control the clutch engagement and improve the vehicle launching quality.