In this study, a hybrid particle swarm optimization (HPSO) approach is presented for enhancing the performance of a three-phase, 12-slot, 19-pole yoke-less axial-field flux-switching permanent magnet (YASA-AFFSPM) motor. The aim of the optimization process is to achieve a motor that demonstrates high efficiency and stable operation. To facilitate this, a finite element analysis model is developed, and a multi-objective optimization function utilizing weight coefficients is created. The variables in this study include the split ratio, stator axial length, sandwiching pole angle, rotor pole angle, permanent magnet arc, and the number of conductors per slot. The optimization objectives encompass efficiency, power factor, cogging torque, and average torque, evaluated under both no-load and load conditions. Findings indicate that the hybrid particle swarm optimization method excels in its search capabilities and convergence speed, resulting in motor designs that align closely with the intended specifications. Finite element simulations further validate the proposed methodology's effectiveness and practicality. Finally, experimental results are presented to confirm the reliability of the suggested algorithm.
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