An Accurate Multi-objective Optimization Strategy for Surface-Mounted Permanent-Magnet Machines Based on Nonlinear Finite-Permeability Subdomain Model

This digest presents an accurate multi-objective optimization strategy for surface-mounted permanent-magnet machines (SMPMMs) by combining a nonlinear finite-permeability subdomain model (FPSM) with an optimization algorithm. First, the nonlinear FPSM is developed by introducing a nonlinear iterative algorithm to consider the magnetic saturation of soft magnetic materials and applied to the SMPMMs. Then, the average torque and the torque ripple are computed by this analytical model. Next, this nonlinear FPSM is combined with the non-dominated sorting genetic algorithm II (NSGA-II) to find the optimal designs for the studied SMPMM. Finally, the electromagnetic performances of one optimal case are validated by the finite-element model to demonstrate the effectiveness of the presented optimization strategy.