Multi-objective Optimization Design of Partitioned Stator Flux-modulation Machine with Particle Swarm Optimization Algorithm

The rich harmonic components in the air gap of the partitioned stator flux modulation(PSFM) machine inevitably produce more iron losses. Therefore, it is very important to use multi-objective optimization method to further improve the efficiency of PSFM machines. By analyzing the harmonic coupling process of permanent magnet magnetic field and armature reaction magnetic field, the mechanism of electromagnetic torque generation is revealed based on the air-gap field modulation theory. At the same time, the influence of the salient pole modulation block on the electromagnetic performance is studied, and the advantages of the topology in non-working harmonic suppression are proved. Secondly, according to the topological parameters of the rotor, the average torque, iron loss and torque ripple are taken as the design objectives, and the response surface methodology(RSM) and particle swarm optimization(PSO) are combined to carry out the multi-objective optimization design. In addition, based on the finite element simulation, the electromagnetic performance of the PSFM machine before and after optimization is compared, which shows that the proposed method plays an important role on reducing iron losses. Finally, a prototype is manufactured and tested to verify the correctness of the theoretical analysis.