Optimal Design of Surface-Mounted Permanent Magnet Motor With Multi-Level Magnet Combination Using Analytical Method

In this article, the surface-mounted permanent magnet motor (SPMM), which uses multi-level magnet combination to improve air-gap magnetic field distribution, is modeled and optimized based on analytical method (AM). The multi-level magnets adopt the specific combination of NdFeB and ferrite with different remanences to reduce the harmonics of the air-gap magnetic field and the torque ripple. First, the analytical modeling method of SPMM with multi-level NdFeB and ferrite magnets is presented, and the results are compared with finite element method (FEM) results. To further improve the performance, the manta ray foraging optimization (MRFO) algorithm is used to optimize the average torque, torque ripple, and magnet cost, taking the angles of different magnets as variables. The effectiveness of the optimization approach is verified by comparing the fitness and computation with the particle swarm optimization (PSO) algorithm. Finally, a prototype is manufactured based on the optimization results, and the tested electromagnetic performance is compared with the FEM and analytical results.