Optimal Conduction Angles of Switched Reluctance Motors Over the Entire Operating Range

The performance of Switched Reluctance Machines (SRMs) is strongly influenced by the selection of conduction angles, which determine torque quality and efficiency across varying operating conditions. This paper presents a comprehensive optimization framework that jointly considers speed, reference current, and dc-link voltage to compute operating– point–dependent conduction angles over the entire operating map. An offline genetic algorithm (GA) is used to formulate two single-objective functions, maximizing the average torque and maximizing the ratio of average torque to RMS torque ripple. The optimized angles are stored in a lookup table (LUT) for real-time deployment. A fixed-parameter current controller with strong tracking performance is used to validate the optimum conduction angles. Simulation and experimental results on a three-phase 12/8 SRM demonstrate a significant improvement in torque quality, achieving an average torque ripple reduction of 70% while maintaining similar or higher average torque compared to conventional analytical angle selection. The proposed approach offers a practical solution to wide-range SRM operation in applications where torque quality is critical, such as traction and propulsion.