Online Inductance Identification of Permanent Magnet Synchronous Motor Based on Extended Kalman Filter With Dead-Time Compensation

A dq-axis inductance identification method is proposed for permanent magnet synchronous motor (PMSM) , which is based on an extended Kalman filter with dead-time compensation. The proposed method is intended to estimate the disturbance voltage in the dq coordinate system, which is caused by dead-time and non-ideal switching characteristics of the power devices. The proposed method is achieved by means of parametric calculation, which is then fed into the Kalman filter to compensate the dead-time effect. Furthermore, the sensitivity analyses of the input parameters demonstrate that the accuracy of the extended Kalman filter discrimination is contingent on the precision of the input parameters. The effectiveness of the proposed method is demonstrated by simulation results.

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Publication Details

Published
2025-06-02
DOI
https://doi.org/10.34746/epe2025-0243
Primary Topic
Sensorless Control of Electric Motors
Type
article
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article

Online Inductance Identification of Permanent Magnet Synchronous Motor Based on Extended Kalman Filter With Dead-Time Compensation

Sensorless Control of Electric Motors
article

Online Inductance Identification of Permanent Magnet Synchronous Motor Based on Extended Kalman Filter With Dead-Time Compensation

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Abstract

A dq-axis inductance identification method is proposed for permanent magnet synchronous motor (PMSM) , which is based on an extended Kalman filter with dead-time compensation. The proposed method is intended to estimate the disturbance voltage in the dq coordinate system, which is caused by dead-time and non-ideal switching characteristics of the power devices. The proposed method is achieved by means of parametric calculation, which is then fed into the Kalman filter to compensate the dead-time effect. Furthermore, the sensitivity analyses of the input parameters demonstrate that the accuracy of the extended Kalman filter discrimination is contingent on the precision of the input parameters. The effectiveness of the proposed method is demonstrated by simulation results.

Huazhong University of Science and Technology (CN)
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Sensorless Control of Electric Motors
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