This thesis developed a co-design optimization framework for Switched Reluctance Motors (SRM) where geometric and control parameters are... Show moreThis thesis developed a co-design optimization framework for Switched Reluctance Motors (SRM) where geometric and control parameters are jointly optimized to improve the overall performance of the motor. This algorithm aims to increase the average torque, decrease the ripple of the torque profile, and enhance operating efficiency as well as acoustic noise. This co-design methodology allows the motor electromagnetic design to be combined with the control strategy and presents a solution for multi-physics optimization. A magnetic equivalent circuit (MEC) based approach is proposed to analyze the electromagnetic characteristics which greatly improves the accuracy over conventional MEC for arbitrary geometries. The natural frequencies of the stator system are identified using a system approach, which is suitable for motors with complex frames. The vibration response and acoustic noise prediction are analyzed and evaluated by the analytical approach.
To demonstrate the effectiveness of this approach, case studies were performed that compare optimized SRM designs obtained from their framework to those designed traditionally. Experimental validation is performed to evaluate the accuracy of the proposed approach. Show less
