IEEE Open Journal of Industry Applications (Jan 2024)

Refinement of Analytical Current Waveform for Acoustic Noise Reduction in Switched Reluctance Motor

  • Fares S. El-Faouri,
  • Yifei Cai,
  • Akira Chiba

DOI
https://doi.org/10.1109/OJIA.2024.3434668
Journal volume & issue
Vol. 5
pp. 325 – 337

Abstract

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In this article, a refinement algorithm of the current waveform that flattens the radial-force sum in switched reluctance motors is proposed. Flattening the radial-force sum eliminates the multiples of the third radial-force component. These components excite the breathing mode vibration, which is typically the dominant vibration in switched reluctance motors with a high number of poles. The previously proposed analytical current derivation for flattening the radial-force sum neglects magnetic saturation, limiting its applicability to low-torque region. Consequently, for high-torque saturation conditions, the previous waveform shaping degrades in flattening the radial-force sum. The proposed refinement of the analytical current waveform addresses this limitation, enabling effective radial-force sum flattening even under high-torque conditions. Additionally, the proposed current exhibits significantly lower peaks than those of the flattening methods at high-torque region in the literature, mitigating the need for higher-rated inverters. Finite element analysis and experimental validation verify the effectiveness of the proposed method.

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