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Parameter Identification For Inter Turn Fault Detection In Permanent-Magnet Synchronous Motors Using Stator Flux Linkage DC Offset Monitoring

Upadhyay, Akanksha LU ; Reinap, Avo LU and Alakula, Mats LU orcid (2023) 14th IEEE International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives, SDEMPED 2023 p.498-504
Abstract

The parameters of PMSM with inter-turn fault are identified using a time-stepping finite element method (FEM). Analytical expressions (AE) uses the estimated parameters for fault analysis similar to FEM analysis. The fault waveforms, terminal voltages, obtained from the AE models are used for inter turn fault (ITF) detection, using Stator Flux Linkage DC offset (SFDO). A comparison is made between the SFDOs obtained using AE with two sets of parameters and experimental results under different fault severity. The difference in parameter selection depends on the fault severity in induced voltage waveform and in all three phases, which makes AE-based fault modeling and its detection more accurate compared to the case where only the no load... (More)

The parameters of PMSM with inter-turn fault are identified using a time-stepping finite element method (FEM). Analytical expressions (AE) uses the estimated parameters for fault analysis similar to FEM analysis. The fault waveforms, terminal voltages, obtained from the AE models are used for inter turn fault (ITF) detection, using Stator Flux Linkage DC offset (SFDO). A comparison is made between the SFDOs obtained using AE with two sets of parameters and experimental results under different fault severity. The difference in parameter selection depends on the fault severity in induced voltage waveform and in all three phases, which makes AE-based fault modeling and its detection more accurate compared to the case where only the no load waveform is used for all three phases.

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Please use this url to cite or link to this publication:
author
; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
back emf, EV, FEM, ITF, Parameter identification, PMSM, SFDO, stator faults, stator flux linkage
host publication
Proceedings of the 2023 IEEE 14th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives, SDEMPED 2023
editor
Zarri, Luca and Lee, Sang Bin
pages
7 pages
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
14th IEEE International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives, SDEMPED 2023
conference location
Chania, Greece
conference dates
2023-08-28 - 2023-08-31
external identifiers
  • scopus:85175266903
ISBN
9798350320770
DOI
10.1109/SDEMPED54949.2023.10271486
language
English
LU publication?
yes
id
32e420c1-7f82-4508-afc7-32161aced0c9
date added to LUP
2023-12-18 13:12:22
date last changed
2024-02-09 11:33:04
@inproceedings{32e420c1-7f82-4508-afc7-32161aced0c9,
  abstract     = {{<p>The parameters of PMSM with inter-turn fault are identified using a time-stepping finite element method (FEM). Analytical expressions (AE) uses the estimated parameters for fault analysis similar to FEM analysis. The fault waveforms, terminal voltages, obtained from the AE models are used for inter turn fault (ITF) detection, using Stator Flux Linkage DC offset (SFDO). A comparison is made between the SFDOs obtained using AE with two sets of parameters and experimental results under different fault severity. The difference in parameter selection depends on the fault severity in induced voltage waveform and in all three phases, which makes AE-based fault modeling and its detection more accurate compared to the case where only the no load waveform is used for all three phases.</p>}},
  author       = {{Upadhyay, Akanksha and Reinap, Avo and Alakula, Mats}},
  booktitle    = {{Proceedings of the 2023 IEEE 14th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives, SDEMPED 2023}},
  editor       = {{Zarri, Luca and Lee, Sang Bin}},
  isbn         = {{9798350320770}},
  keywords     = {{back emf; EV; FEM; ITF; Parameter identification; PMSM; SFDO; stator faults; stator flux linkage}},
  language     = {{eng}},
  pages        = {{498--504}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{Parameter Identification For Inter Turn Fault Detection In Permanent-Magnet Synchronous Motors Using Stator Flux Linkage DC Offset Monitoring}},
  url          = {{http://dx.doi.org/10.1109/SDEMPED54949.2023.10271486}},
  doi          = {{10.1109/SDEMPED54949.2023.10271486}},
  year         = {{2023}},
}