Aiming at the problems of large torque ripple in Switched Reluctance Motor and traditional optimization design that only starts from the motor without considering the drive control strategy, a system-level multi-objective optimization design strategy for SRM considering Model Predictive Torque Control is proposed by simultaneously considering the motor structure parameters and control parameters. Firstly, the structural parameters of SRM were designed according to the design requirements and MPTC was adopted as the control method to determine the initial values and variation ranges of the motor structure and control parameters; Secondly, an SRM design model considering MPTC was established, and the relationship between structural parameters and prediction models was determined through magnetic circuit analysis. The optimization process of the motor was determined with torque ripple, average torque current ratio, and copper loss as optimization objectives. Sensitivity analysis of structural and control parameters was conducted through orthogonal experiments, and decision variables were selected based on the analysis results. Taguchi algorithm was used for multi-objective optimization of decision variables; Finally, in order to verify the effectiveness of the method, simulation verification was conducted, and a prototype was trial produced based on the optimization results. The experimental results showed that compared with the conventional design, the optimization results reduced the peak motor phase current by 33%, increased the average torque ampere ratio by 33.3%, and reduced torque ripple by 26.3%. The rationality and effectiveness of the optimization method were verified through experiments.