An Improved MRAS-Based Multi-parameter Identification Method for Permanent Magnet Synchronous Motor Drives

The rank deficiency of conventional MRAS leads to the parameter identification error. To address this problem, a model reference adaptive multi-parameter identification method based on the current incremental state equation is proposed. Taking advantage of the fact that the motor electrical time constant is much smaller than the mechanical time constant, the current incremental state equation is constructed and used as the adjustable model of the model reference adaptive system. Thus, the resistance and inductance parameter accurate identification can be realized in the case of the flux parameter is completely unknown, and the identification error caused by the rank deficiency issue is avoided. The proposed method does not need to inject additional excitation signal. Experimental validation demonstrates that the proposed method can accurately identify motor parameters.

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Publication Details

Published
2024-12-20
DOI
https://doi.org/10.1109/ceect63656.2024.10898432
Citations
1
Primary Topic
Electric Motor Design and Analysis
Type
article
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An Improved MRAS-Based Multi-parameter Identification Method for Permanent Magnet Synchronous Motor Drives

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1 citations
Electric Motor Design and Analysis
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article

An Improved MRAS-Based Multi-parameter Identification Method for Permanent Magnet Synchronous Motor Drives

Lei Shi, Yuqing Huang, Shengqi Huang, Yuanwei Zhang, Bin Chang, Sizhe Hu
article en
1 citations

Abstract

The rank deficiency of conventional MRAS leads to the parameter identification error. To address this problem, a model reference adaptive multi-parameter identification method based on the current incremental state equation is proposed. Taking advantage of the fact that the motor electrical time constant is much smaller than the mechanical time constant, the current incremental state equation is constructed and used as the adjustable model of the model reference adaptive system. Thus, the resistance and inductance parameter accurate identification can be realized in the case of the flux parameter is completely unknown, and the identification error caused by the rank deficiency issue is avoided. The proposed method does not need to inject additional excitation signal. Experimental validation demonstrates that the proposed method can accurately identify motor parameters.

Shanghai Power Equipment Research Institute (CN)
Affordable and clean energy
Openalex Percentile: Top 43%
Electric Motor Design and Analysis
0.21
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