A sliding mode speed and position observer for a surface-mounted PMSM.

Adaptive synchronization filter Quadrature phase-lock loop Sliding mode observer Surface-mounted PMSM

Journal

ISA transactions
ISSN: 1879-2022
Titre abrégé: ISA Trans
Pays: United States
ID NLM: 0374750

Informations de publication

Date de publication:
Apr 2019
Historique:
received: 12 06 2018
revised: 22 09 2018
accepted: 09 11 2018
pubmed: 12 12 2018
medline: 12 12 2018
entrez: 12 12 2018
Statut: ppublish

Résumé

To improve the speed and position observation performance of a Surface-Mounted Permanent Magnet Synchronous Motor (SM-PMSM), an improved sliding mode observer (SMO) based on the adaptive synchronization filter (ASF) and quadrature phase-lock loop (QPLL) is proposed. An adaptive synchronous filter based on feedback rotor position estimation from a QPLL is proposed to extract the fundamental signal of the back electromotive force (back-EMF). Then, a QPLL is linked to calculate the rotor position and speed according to the fundamental signal of the back-EMF, in order to effectively suppress the estimated harmonics and chattering and improve the observation accuracy of speed and position. Finally, the effectiveness and feasibility of the proposed observer approach are verified by simulation and dSPACE.

Identifiants

DOI: 10.1016/j.isatra.2018.11.011 PMID: 30528125
pubmed: 30528125
pii: S0019-0578(18)30446-4
doi: 10.1016/j.isatra.2018.11.011
pii:
doi:

Types de publication

Journal Article

Langues

eng

Pagination

17-27

Informations de copyright

Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Auteurs

Yong Chen (Y)

School of Automation and Engineering and, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China; Institute of Electric Vehicle Driving System and Safety Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China. Electronic address: ychencd@uestc.edu.cn.

Meng Li (M)

School of Automation and Engineering and, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China; Institute of Electric Vehicle Driving System and Safety Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China.

Yu-Wen Gao (YW)

School of Automation and Engineering and, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China; Institute of Electric Vehicle Driving System and Safety Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China.

Zhang-Yong Chen (ZY)

School of Automation and Engineering and, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China; Institute of Electric Vehicle Driving System and Safety Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China.

Classifications MeSH