Torque Ripple Reduction by Optimizing Magnet Shape in Axial Gap Motor

Abstract

　This paper proposes a method to reduce torque ripple in axial gap motor by multi-objective optimization of magnet shape using Fourier series expansion. Torque ripple is a problem because it causes vibration and noise and deteriorates the accuracy of position and speed control. Previously, the torque ripple was reduced while maintaining almost the same torque by designing the magnet in the shape of multiplying wave. However, it is necessary to optimize the function that constitutes the magnet shape to obtain a better one. In this study, the functions constituting the magnet shape are expressed as Fourier series, and a genetic algorithm is used to optimize the combination of their coefficients. As a result, the proposed model was almost equivalent to the average torque of the basic model, and the torque ripple was significantly reduced. Furthermore, fillets were applied to it to verify the effect of the fillets on each characteristic.