The parameter uncertainty of permanent magnet synchronous motor (PMSM) drive system and the nonlinearity of inverter will reduce the robustness of motor speed and lead to the drastic fluctuation of electric vehicle speed. In order to improve the response performance and robustness of PMSM drive system for electric vehicles, a model-free adaptive backstepping control ( MF-ABC) is proposed. First, based on the algebraic estimation method of model-free control, an ultra-local model disturbance estimator is established. Second, based on the adaptive backstepping control framework, MF-ABC control suitable for high reliability operation of PMSM drive system is constructed. The results show that the proposed controller can observe, estimate and eliminate all kinds of uncertainties, including unmodeled dynamics and external disturbances. The disturbance value estimated by MF-ABC can be used to describe uncertainty and analysis error. The proposed scheme improves the calculation efficiency in real time and achieves the research goal of high performance and robust operation of the vector controlled PMSM drive system MTPA mode. Through dSPACE bench test, compared with traditional backstepping control, the proposed MF-ABC achieves 22% improvement in the torque disturbance suppression capability of PMSM and 0. 02 s increase in the step response speed. The experimental results show that MF-ABC has strong disturbance suppression capability and fast response performance.