Torque Ripple Mitigation Strategy for Bearingless Flux-Reversal Slice Motors Considering Rotor Eccentricity

Bearingless flux-reversal slice motor (BFRSM) is a compact and innovative motor known for its robust rotor design and simplified manufacturing processes. However, inherent design features like the double-salient air gap and consequent-pole stator teeth cause increased torque ripple, leading to fluctuations in speed and rotor suspension, which ultimately compromise overall performance. The existing literature has not given a comprehensive research on torque ripple mitigation strategy for flux-reversal motors under conditions of rotor eccentricity and suspension currents. To address this issue, this article presents a torque ripple mitigation strategy based on a comprehensive torque ripple model specific to BFRSM. As the foundation for the torque model, this article derives the electromotive force (EMF) model of BFRSM by analyzing the magnetic field of the air gap, with a double-pole structure under eccentric conditions. Then, the torque ripple model corresponding to each order harmonics and reflecting the impact of rotor eccentricity is derived. Building on this model, the proposed strategy designs compensation harmonic currents with minimal copper loss to reduce torque ripple and enhance the performance of BFRSM. Furthermore, to enhance harmonic current control performance and improve system stability, the impulse invariant method is applied in the digital implementation. Experimental validation on a BFRSM prototype demonstrates the effectiveness of the strategy in mitigating torque ripple under both steady-state and transient operational conditions. The results indicate a 38% reduction in torque ripple under both normal and eccentric conditions.

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Publication Details

Journal
IEEE Transactions on Transportation Electrification
Published
2025-03-11
DOI
https://doi.org/10.1109/tte.2025.3550169
Citations
1
Primary Topic
Iterative Learning Control Systems
Type
article
Field-Weighted Citation Impact
1.21

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article

Torque Ripple Mitigation Strategy for Bearingless Flux-Reversal Slice Motors Considering Rotor Eccentricity

Wubin Kong, Ronghai Qu, Dawei Li, Zirui Liu et al.
1 citations
IEEE Transactions on Transportation Electrification
Iterative Learning Control Systems
1.21
article

Torque Ripple Mitigation Strategy for Bearingless Flux-Reversal Slice Motors Considering Rotor Eccentricity

Wubin Kong, Ronghai Qu, Dawei Li, Zirui Liu, Jiayun Liu
article en
1 citations

Abstract

Bearingless flux-reversal slice motor (BFRSM) is a compact and innovative motor known for its robust rotor design and simplified manufacturing processes. However, inherent design features like the double-salient air gap and consequent-pole stator teeth cause increased torque ripple, leading to fluctuations in speed and rotor suspension, which ultimately compromise overall performance. The existing literature has not given a comprehensive research on torque ripple mitigation strategy for flux-reversal motors under conditions of rotor eccentricity and suspension currents. To address this issue, this article presents a torque ripple mitigation strategy based on a comprehensive torque ripple model specific to BFRSM. As the foundation for the torque model, this article derives the electromotive force (EMF) model of BFRSM by analyzing the magnetic field of the air gap, with a double-pole structure under eccentric conditions. Then, the torque ripple model corresponding to each order harmonics and reflecting the impact of rotor eccentricity is derived. Building on this model, the proposed strategy designs compensation harmonic currents with minimal copper loss to reduce torque ripple and enhance the performance of BFRSM. Furthermore, to enhance harmonic current control performance and improve system stability, the impulse invariant method is applied in the digital implementation. Experimental validation on a BFRSM prototype demonstrates the effectiveness of the strategy in mitigating torque ripple under both steady-state and transient operational conditions. The results indicate a 38% reduction in torque ripple under both normal and eccentric conditions.

IEEE Transactions on Transportation ElectrificationVol. 11(4)
Huazhong University of Science and Technology (CN)
National Natural Science Foundation of China
Climate action
Openalex Percentile: Top 24%
Iterative Learning Control Systems
1.21
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