Modeling and Control Approach for Dual Clutch Transmission Vehicles Starting Process Based on State-Dependent Autoregressive With Exogenous Model

Abstract

To solve the difficulties of modeling the starting system of dual clutch transmission (DCT) vehicles, a state-dependent autoregressive with exogenous variables (SD-ARX) model whose functional coefficients are approximated by sets of radial basis function (RBF) networks is proposed to describe the dynamic characteristics of DCT vehicles starting process in this study. The validity of this modelling approach is verified via a real vehicle test. On this basis, a nonlinear predictive controller based on SD-ARX model is designed. In addition, the physical constraints of this system, including control variables (change rate of engine torque and clutch torque) and state variables (engine speed and clutch speed), are also taken into account during the controller design process via limiting the relevant parameters in particle swarm optimization or setting saturation demand in control program. To verify the validity and merits of the proposed control approach, many sets of simulation analysis in different driving intentions are conducted. Simulation results shown that: the proposed control approach can well control the starting process of DCT vehicles and effectively reflect the demand of driver's intention; compared with the conventional control method, SD-ARX-MPC can improve the starting performance; the proposed approach is robust to a certain extent according to simulation results under changed starting conditions.