LAPSE:2023.27730
Published Article
LAPSE:2023.27730
Real-Time Multiparameter Identification of a Salient-Pole PMSM Based on Two Steady States
Minglei Zhou, Long Jiang, Chenchen Wang
April 4, 2023
Real-time multiparameter identification has been widely investigated in relation to high-performance control and fault diagnosis of salient-pole permanent magnet synchronous motors (PMSMs). However, it is rank-deficient for simultaneously estimating flux, resistance, and dq-axis inductances based on one steady state under maximum torque per ampere (MTPA) control, which will cause the ill-convergence problem in the results. This paper proposes a new method to solve the rank deficiency problem in the multiparameter identification of salient-pole PMSMs in systems where the motor working conditions do not change frequently. For this type of system, a second steady state is constructed in order to meet the full-rank conditions for multiparameter identification and minimize the torque ripple. Furthermore, in order to reduce the influence of inductance variations, a better shift direction from the first steady state to the second is ensured based on the analysis of the theoretical error. Simulation and experimental results show that the proposed method demonstrates good identification performance.
Keywords
error analysis, multiparameter identification, salient-pole PMSM, steady state
Suggested Citation
Zhou M, Jiang L, Wang C. Real-Time Multiparameter Identification of a Salient-Pole PMSM Based on Two Steady States. (2023). LAPSE:2023.27730
Author Affiliations
Zhou M: Institute of Power Electronics, School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China
Jiang L: Institute of Power Electronics, School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China
Wang C: Institute of Power Electronics, School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China
Journal Name
Energies
Volume
13
Issue
22
Article Number
E6109
Year
2020
Publication Date
2020-11-21
Published Version
ISSN
1996-1073
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PII: en13226109, Publication Type: Journal Article
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LAPSE:2023.27730
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doi:10.3390/en13226109
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