Optimization Transmission Efficiency with Driver Intention for Automotive Continuously Variable Transmission under Slip Mode

Abstract

This study proposes and experimentally validates an optimal integrated system to control the automotive continuously variable transmission (CVT) by Model Predictive Control (MPC) to achieve its expected transmission efficiency range. The control system framework consists of top and bottom layers. In the top layer, a driving intention recognition system is designed on the basis of fuzzy control strategy to determine the relationship between the driver intention and CVT target ratio at the corresponding time. In the bottom layer, a new slip state dynamic equation is obtained considering slip characteristics and its related constraints, and a clamping force bench is established. Innovatively, a joint controller based on model predictive control (MPC) is designed taking internal combustion engine torque and slip between the metal belt and pulley as optimization dual targets. A cycle is attained by solving the optimization target to achieve optimum engine torque and the input slip in real-time. Moreover, the new controller provides good robustness. Finally, performance is tested by actual CVT vehicles. Results show that compared with traditional control, the proposed control improves vehicle transmission efficiency by approximately 9.12%–9.35% with high accuracy.

Research on Clamping Force Control of CVT for Electric Vehicles Based on Slip Characteristics

“…The research results show that controlling the slip can improve CVT efficiency [ 29 , 30 , 31 ]. In the literature [ 32 , 33 , 34 , 35 ], various controllers such as the adaptive PI controller and LQR controller are designed to improve the effect of slip control. Simulation results show that the designed controller can improve the efficiency of CVT without losing robustness.…”