Dynamic Coordination Control of HEV Unsteady Operating Mode Switching Based on MPC

Abstract

Abstract Aiming at a hybrid electric vehicle (HEV), the impact problem is studied during the mode switching process under non-steady-state operating conditions. Firstly, the system dynamics model is established, the dynamic characteristics of unsteady conditions are analyzed, the BP neural network engine torque estimation model based on genetic algorithm optimization is established, and the engine torque is estimated online. MG1 torque coordination control and MG2 active compensation control are adopted, a mode switching coordination control strategy based on model prediction is proposed. The MATLAB / Simulink simulation platform is used to verify the effectiveness of the control algorithm. The simulation results show that the coordinated control strategy can effectively achieve the output torque compensation of the drive motor. The engine is actually close to the target torque. Compared with the uncoordinated control, During the speed synchronization phase, the maximum impact of the vehicle was reduced by 60.4%.