Cogging Torque Suppression of Modular Permanent Magnet Machines Using a Semi-Analytical Approach and Artificial Intelligence

Abstract

The cogging torque of permanent magnet machines with a modular stator is affected by additional harmonic components due to the segmentation of the stator lamination. This paper proposes a novel approach based on the shaping of the stator tooth tips with sinusoidal profiles to minimize the cogging torque of such machines. A theoretical study and a design formula are proposed to determine the spatial frequency of the sinusoidal profiles, while an optimization procedure based on genetic algorithm and artificial neural networks is adopted to determine their amplitudes and phase shifts. The proposed method is validated through finite element analysis considering two different case studies. Also, a comparison with other approaches from the literature is presented to highlight the effectiveness of the proposed technique. Finally, an additional analysis is reported to demonstrate the effectiveness of the proposed method against manufacturing and assembling tolerances.

Keywords

• Artificial neural networks
• cogging torque
• finite-element analysis
• genetic algorithm
• modular stators
• permanent magnet synchronous motors