Given its highly coupled multi-power sources with diverse dynamic response characteristics, the mode transition process of a power-split Hybrid Electric Vehicle (HEV) can easily lead to unanticipated passenger-felt jerks. Moreover, difficulties in parameter estimation, especially power-source dynamic torque estimation, result in new challenges for jerk reduction. These two aspects entangle with each other and constitute a complicated coupling problem which obstructs the realization of a valid anti-jerk method. In this study, a vehicle dynamics model with reference to a data-driven modeling method is first established, integrating a full-time artificial neural network engine dynamic model that can accurately predict engine dynamic torque. Then the essential reason for the occurrence of vehicle jerks in real driving conditions is analyzed. Finally, to smooth the mode transition process, a more practical anti-jerk strategy based on power-source torque changing rate limitation (TCRL) is proposed. Verification studies indicate that the data-driven vehicle dynamics model has enough accuracy to reflect the vehicle dynamic characteristics, and the proposed TCRL strategy could reduce the vehicle jerk by up to 85.8%, without any sacrifice of vehicle performance. This research provides a feasible method for precise modeling of vehicle dynamics and a reference for improving the riding comfort of hybrid electric vehicles.

To improve the contradiction between vehicle dynamic performance and ride comfort by using the motor active output torque compensation method to reduce the torsional vibration of the hybrid electric vehicle (HEV) powertrain, an active multiobjective real-time vibration control (AMRVC) algorithm based on model prediction control (MPC) is proposed in this paper, and the current mainstream parallel HEV is taken as the research object to verify the proposed algorithm. Firstly, the torsional vibration model of the parallel HEV powertrain is established, simplified, and verified according to the experimental data, which provides the basis for the multimode adaptability and the application of the controller. Then, based on the state space equation of the torsional vibration system, the MPC controller considering the balance between ride comfort and power performance is designed, which can meet the multiobjective and real-time control effect of the hybrid power system while realizing the active vibration control. Finally, the effectiveness and real-time performance of the AMRVC algorithm are verified by multimode simulation analysis and hardware-in-the-loop (HIL) experiment. The simulation results show that the AMRVC algorithm based on MPC has good real-time application conditions, which can well coordinate the multiobjective requirements of vehicle ride comfort and dynamic performance, and remarkably improve the torsional vibration response of the powertrain by more than 55% in all HEV typical operating modes.