Model Reference Adaptive Control Based on Adjustable Reference Model during Mode Transition for Hybrid Electric Vehicles

Abstract

Hybrid elective vehicles (HEVs) operate in multiple driving modes, e.g., motor driving mode, engine driving mode, and combined driving mode, under various different scenarios. Therefore, mode transition between different driving modes is necessary to ensure high-efficiency operation of HEVs under various running conditions. This paper proposes adjustable reference model (ARM)-based model reference adaptive control (MRAC) to solve the problems of deviation from driver's intention and lack of adaptability to parameter changes. The driveline dynamics model during mode transition is built and validated. The dynamics in the mode before the mode transition is taken as the reference model whose parameters are estimated online. Thereafter, the adaptive law is derived. Simulation and hardware-in-loop experiments are carried out. The results show that the mode transition performance under varying driver's demand torque is satisfactory in terms of not only vehicle jerk, but also clutch slipping time and frictional loss. And, the controller has good adaptability to different vehicle masses and road slopes. The ability to deal with the disturbance in clutch torque with low frequency is also validated.