Efficient Mode Transition Control for Parallel Hybrid Electric Vehicle With Adaptive Dual-Loop Control Framework

Mode transition control problem in a hybrid powertrain has always been a central concern, because many complicated transient dynamics are involved in this process, such as engine-start, clutch engagement, and actuator control, etc. Especially for a parallel hybrid electric vehicle (HEV), the drivability problem during mode transition process is significant yet challenging to solve. In this paper, a new efficient mode transition control method with adaptive dual-loop control framework is proposed for the clutch engagement in a parallel HEV. Firstly, the expected clutch engaging speed can be calculated by two approaches, optimization method via particle swarm optimization algorithm, and practical method by compromising the transient vehicle jerk and the clutch slipping power, respectively. Utilizing the integral transformation, the demand clutch position trajectory for the inner loop can be obtained. Considering the uncertainties and the backlash in the clutch actuator system, an adaptive state feedback controller is designed in the inner loop. Simulation and experimental results show that the proposed control method can effectively improve the HEV drivability while taking clutch actuator uncertainties into consideration. Furthermore, compared with the control method commonly used in practice, the time of mode transition process can be shortened and vehicle jerk can be controlled within an acceptable range using the proposed method.