Motor parameter auto-identification based on sensorless startup procedure for PMSM drives

Wen Chun Chi, Ming-Yang Cheng, Cheng Lin Li, Ke Han Su, Wen Hong Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In order to automatically identify the electrical parameters of PMSMs, rather than measure the parameters using instruments such as RLC meters, this paper proposes an approach in which the testing voltage is injected into the motor from the drive. Based on the analysis of equivalent circuits of the PMSMs as well as the phase voltage and phase current information recorded from standstill to sensorless control operation, the RLS method is employed to estimate the values of electrical parameters of the PMSMs. Moreover, the automatic motor parameter identification algorithm developed in this paper is also integrated into the open loop startup procedure of the sensorless control drive. Consequently, the proposed automatic motor parameter identification method has attractive features such as fast identification and being highly convenient. In addition, both the proposed automatic motor parameter identification method and the sensorless control drive developed in this paper are implemented using a low-cost 16-bit microcontroller. Two commercial surface-type and interior-type PMSMs are used in the experiments to assess the performance of the proposed approach. Experimental results verify the effectiveness of the proposed automatic motor parameter identification method.

Original languageEnglish
Title of host publicationIECON Proceedings (Industrial Electronics Conference)
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3861-3866
Number of pages6
ISBN (Electronic)9781479940325
DOIs
Publication statusPublished - 2014 Feb 24

Publication series

NameIECON Proceedings (Industrial Electronics Conference)

Fingerprint

Plant startup
Identification (control systems)
Electric potential
Microcontrollers
Equivalent circuits
Testing
Sensorless control
Costs
Experiments

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

Chi, W. C., Cheng, M-Y., Li, C. L., Su, K. H., & Li, W. H. (2014). Motor parameter auto-identification based on sensorless startup procedure for PMSM drives. In IECON Proceedings (Industrial Electronics Conference) (pp. 3861-3866). [7049076] (IECON Proceedings (Industrial Electronics Conference)). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IECON.2014.7049076
Chi, Wen Chun ; Cheng, Ming-Yang ; Li, Cheng Lin ; Su, Ke Han ; Li, Wen Hong. / Motor parameter auto-identification based on sensorless startup procedure for PMSM drives. IECON Proceedings (Industrial Electronics Conference). Institute of Electrical and Electronics Engineers Inc., 2014. pp. 3861-3866 (IECON Proceedings (Industrial Electronics Conference)).
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Chi, WC, Cheng, M-Y, Li, CL, Su, KH & Li, WH 2014, Motor parameter auto-identification based on sensorless startup procedure for PMSM drives. in IECON Proceedings (Industrial Electronics Conference)., 7049076, IECON Proceedings (Industrial Electronics Conference), Institute of Electrical and Electronics Engineers Inc., pp. 3861-3866. https://doi.org/10.1109/IECON.2014.7049076

Motor parameter auto-identification based on sensorless startup procedure for PMSM drives. / Chi, Wen Chun; Cheng, Ming-Yang; Li, Cheng Lin; Su, Ke Han; Li, Wen Hong.

IECON Proceedings (Industrial Electronics Conference). Institute of Electrical and Electronics Engineers Inc., 2014. p. 3861-3866 7049076 (IECON Proceedings (Industrial Electronics Conference)).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Chi WC, Cheng M-Y, Li CL, Su KH, Li WH. Motor parameter auto-identification based on sensorless startup procedure for PMSM drives. In IECON Proceedings (Industrial Electronics Conference). Institute of Electrical and Electronics Engineers Inc. 2014. p. 3861-3866. 7049076. (IECON Proceedings (Industrial Electronics Conference)). https://doi.org/10.1109/IECON.2014.7049076