Parameter Identification For Inter Turn Fault Detection In Permanent-Magnet Synchronous Motors Using Stator Flux Linkage DC Offset Monitoring
(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.
(Less)
- author
- Upadhyay, Akanksha LU ; Reinap, Avo LU and Alakula, Mats LU
- organization
- publishing date
- 2023
- 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}}, }