The mode transition of single-shaft parallel hybrid electric vehicles (HEVs) between engine and motor has an important impact on power and drivability. Especially, in the process of mode transition from the pure motor-drive operating mode to the only engine-drive operating mode, the motor starting engine and the clutch control problem have an important influence on driving quality, and solutions have a bit of room for improving dynamic performance. In this paper, a novel mode transition control method is proposed to guarantee a fast and smooth mode transition process in this regard. First, an adaptive sliding mode control (A-SMC) strategy is presented to obtain the desired torque trajectory of the clutch transmission. Second, a proportional-integral (PI) observer is designed to estimate the actual transmission torque of the clutch. Meanwhile, a fractional order proportional-integral-differential (FOPID) controller with the optimized control parameters by particle swarm optimization (PSO) is employed to realize the accurate position tracking of the direct current (DC) motor clutch so as to ensure clutch transmission torque tracking. Finally, the effectiveness and adaptability to system parameter perturbation of the proposed control approach are verified by comparison with the traditional control strategy in a MATLAB environment. The simulation results show that the driving quality of the closed-loop system using the proposed control approach is obviously improved due to fast and smooth mode transition process and better adaptability.

A fast and smooth mode transition process for parallel hybrid electric vehicles (HEVs) can improve vehicle drivability. At the same time, system uncertainty resulting from friction, gearbox, parameter perturbation, production deviations, and external disturbance of the mode transition process makes control design challenges. In this regard, this paper introduces a novel efficient hierarchical robust adaptive mode transition control strategy to achieve an accurate and fast engagement of the clutch of a parallel HEV during mode transition in the case of uncertain system parameters and unmeasurable actual clutch torque in this paper. At the upper level of the controller, a robust adaptive sliding mode control (RASMC) is proposed to calculate the clutch transmitted required torque based on the current states of the electric motor (EM) and engine, and the control parameters are optimized via the particle swarm optimization (PSO) algorithm by compromising the vehicle jerk and the clutch slipping energy loss. Moreover, a fuzzy controller is designed to calculate the expected clutch engaging speed by employing the deviation of the desired and actual clutch torques, and the actual clutch torque is not a measured value but an estimate obtained by a proportional-integral (PI) observer. At the lower level, an adaptive finite-time control (AFTC) scheme is developed to overcome the gear backlash, parameter perturbation, and external disturbance during the clutch position tracking process. The effectiveness and advantage of the proposed control strategy are verified by both MATLAB/Simulink simulations and the hardware-in-loop (HIL) test.

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