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March 17, 2026Transactions of the Institute of Systems Control and Information Engineers0 citationsOpen Access

Angular Velocity Estimation for Brushless DC Motors Based on Particle Filter with Likelihood Reflecting Misalignment of Hall Sensors and Magnetic Poles

NMNaoto MutoYCYuichi CHIDAMTMasaya TANEMURA

Key Points

  • To improve angular velocity estimation for brushless DC motors by addressing Hall sensor and magnetic pole misalignment.
  • Utilized a particle filter for estimation.
  • Developed a likelihood design reflecting misalignment distribution.
  • Conducted preliminary experiments to obtain misalignment distribution.
  • Performed experiments to validate the estimation performance.
  • Particle filter with designed likelihood showed enhanced estimation accuracy.
  • Misalignment reflection in the likelihood significantly improved outcomes.
  • Experimental validation confirmed the effectiveness of the proposed method.

Abstract

Hall sensors are used to estimate angular velocity of brushless DC motors. However, the estimation performance deteriorates due to misalignment of Hall sensors and magnetic poles on the rotor. The proposed method uses a particle filter to robustly estimate angular velocity against the misalignment. Specifically, the estimation performance is improved by reflecting the distribution of the misalignment in likelihood design of particle filter. Furthermore, the distribution of the misalignment can be easily obtained through preliminary experiments. Experiments verify that the designed likelihood improves estimation performance of the particle filter.

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Cite This Study

Muto et al. (2025) studied this question.

synapsesocial.com/papers/69b8ef36deb47d591b8c53f2https://doi.org/10.5687/iscie.38.261
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