Abstract: In order to quickly and accurately establish the nonlinear model of switched reluctance motor (SRM) and improve the performance of model predictive control (MPC), we propose a model predictive control strategy based on fast Fourier modeling method. On the one hand, Fourier series is used to model the flux and torque characteristics, and the torque prediction model is derived. On the other hand, by integrating the concept of sector division, we streamline motor commutation control and simplify the cost function. By designating just two preselected voltage vectors within each sector, we effectively alleviate the computational load associated with predictive control. In addition, the position and width of the sector can vary according to changes in speed and load, enhancing the applicability of the algorithm. Simulations and experiments are compared with traditional MPC methods, taking into account different operating conditions at low and high speeds as well as sudden changes in speed and load, and the results have shown that the proposed algorithm has a lower torque ripple and a higher torque ampere ratio.