Adjoint-Based Design Optimization of Nonlinear Switched Reluctance Motors

Abstract

This work investigates the application of the adjoint variable method (AVM) to switched reluctance motors (SRMs). A MATLAB toolbox developed by the authors estimates the sensitivities of the required objective function with respect to different geometric design parameters using at most one adjoint simulation. In this work, the AVM evaluates the sensitivities of the x and y components of the magnetic flux density, the phase flux linkage, and the electromagnetic torque of switched reluctance motors with respect to teeth height, yoke thickness, teeth pole arc angle, and teeth taper angle of both stator and rotor. The nonlinearity of the motor magnetic material is taken into consideration. The estimated sensitivities using AVM are compared with those obtained using the more accurate but time intensive central finite differences (CFD). An interior-point optimization algorithm utilizes the sensitivities of the electromagnetic torque of an SRM to maximize the motor static torque profile. Structural mapping technique is used to control the geometric design parameters through the optimization process.