Aiming at the problems of the conventional controller in the absence of parameters or parameter mismatch of industrial motors, the development performance of industrial automation is not satisfied. a model predictive control based on system identification (SI-MPC) for the asynchronous motor of electric vehicle is proposed. Firstly, the idea of model predictive control is introduced. The discrete mathematical model of asynchronous motor is derived, which is regarded as a predictive model for MPC, and online estimation updates its lumped parameters. the model predictive control can be realized without any motor parameters. Simulation and experimental results show that the proposed control strategy has high prediction accuracy. Under the condition that both working conditions and motor parameters are unknown and time-varying, SI-MPC can still achieve excellent control performance under different conditions, which proves the excellent parameter robustness and effectiveness of this method.