System-Level Robust Design Optimization of a Switched Reluctance Motor Drive System Considering Multiple Driving Cycles

In this article, a novel system-level robust design optimization method is presented to improve the performance of switched reluctance motor (SRM) drive systems under multiple operating conditions. Based on typical driving cycles of electric vehicles (EVs), five typical driving modes of the SRM are determined. The optimization objectives in each driving mode are established. The significant parameters of the motor and controller of each driving mode are selected as the optimization variables by using the sensitivity analysis. In order to simplify the optimization process, correlation analysis is performed to determine the coherence of the objective functions of all driving modes. Then, a sequential Taguchi method is applied to find an optimal design which is less sensitive to the noise factors. To verify the effectiveness of the proposed method, an SRM drive system applied in EVs with a 12/10 SRM and angle position control method is investigated. It is found that the proposed method can significantly reduce the torque ripple and improve the comprehensive performance. Finally, a 12/10 SRM is prototyped and tested to validate the simulation results.

Automated summary

The article introduces a novel system-level robust design optimization method for improving the performance of SRM drive systems across various operating conditions. By optimizing the significant parameters of the motor and controller under different driving modes, the proposed method successfully reduces torque ripple and enhances overall performance. The effectiveness of the method is verified through simulation and prototype testing.