ANN-based system for inter-turn stator winding fault tolerant DTC for induction motor drives

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

10 Citations (Scopus)

Abstract

Direct Torque Control (DTC) scheme uses the stator resistance of the machine for the estimation of stator flux. The variation of stator resistance, due to stator winding turn fault, creates an error in the estimated stator flux position that may subsequently cause a failure of the complete drive system. This paper proposes the possibility of developing a remedial operating strategy using artificial neural network (ANN), which ensures a fault tolerance of inter-turn stator winding fault in the direct torque control (DTC) for induction motor drives. The proposed fault tolerant approach is achieved using a strategy that detects inter-turn stator winding fault, identifies fault severity and improves the DTC performance in the presence of incipient stator winding turn fault. The fault tolerant system is obtained by tuning the stator resistance to make the DTC strategy more robust and precise. This allows continuous disturbance-free operation of the induction motor drives even with existing inter-turn stator winding faults. This strategy is simple to implement, does not require new sensors or changes in the standard drive system. Experimental implementation is demonstrated for the validity of the proposed idea.

Original languageEnglish
Title of host publication2015 17th European Conference on Power Electronics and Applications, EPE-ECCE Europe 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9789075815221
DOIs
Publication statusPublished - 27 Oct 2015
Event17th European Conference on Power Electronics and Applications, EPE-ECCE Europe 2015 - Geneva, Switzerland
Duration: 8 Sep 201510 Sep 2015

Other

Other17th European Conference on Power Electronics and Applications, EPE-ECCE Europe 2015
CountrySwitzerland
CityGeneva
Period8/9/1510/9/15

Fingerprint

Torque control
Induction motors
Stators
Neural networks
Fluxes
Fault tolerance
Tuning

Keywords

  • Artificial Neural Network
  • Direct Torque Control
  • Fault Tolerance
  • Induction motor
  • Winding fault

ASJC Scopus subject areas

  • Fuel Technology
  • Electrical and Electronic Engineering
  • Energy Engineering and Power Technology

Cite this

Khalil, S., Abu-Rub, H., & Iqbal, A. (2015). ANN-based system for inter-turn stator winding fault tolerant DTC for induction motor drives. In 2015 17th European Conference on Power Electronics and Applications, EPE-ECCE Europe 2015 [7309182] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EPE.2015.7309182

ANN-based system for inter-turn stator winding fault tolerant DTC for induction motor drives. / Khalil, Shady; Abu-Rub, Haitham; Iqbal, Atif.

2015 17th European Conference on Power Electronics and Applications, EPE-ECCE Europe 2015. Institute of Electrical and Electronics Engineers Inc., 2015. 7309182.

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

Khalil, S, Abu-Rub, H & Iqbal, A 2015, ANN-based system for inter-turn stator winding fault tolerant DTC for induction motor drives. in 2015 17th European Conference on Power Electronics and Applications, EPE-ECCE Europe 2015., 7309182, Institute of Electrical and Electronics Engineers Inc., 17th European Conference on Power Electronics and Applications, EPE-ECCE Europe 2015, Geneva, Switzerland, 8/9/15. https://doi.org/10.1109/EPE.2015.7309182
Khalil S, Abu-Rub H, Iqbal A. ANN-based system for inter-turn stator winding fault tolerant DTC for induction motor drives. In 2015 17th European Conference on Power Electronics and Applications, EPE-ECCE Europe 2015. Institute of Electrical and Electronics Engineers Inc. 2015. 7309182 https://doi.org/10.1109/EPE.2015.7309182
Khalil, Shady ; Abu-Rub, Haitham ; Iqbal, Atif. / ANN-based system for inter-turn stator winding fault tolerant DTC for induction motor drives. 2015 17th European Conference on Power Electronics and Applications, EPE-ECCE Europe 2015. Institute of Electrical and Electronics Engineers Inc., 2015.
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AB - Direct Torque Control (DTC) scheme uses the stator resistance of the machine for the estimation of stator flux. The variation of stator resistance, due to stator winding turn fault, creates an error in the estimated stator flux position that may subsequently cause a failure of the complete drive system. This paper proposes the possibility of developing a remedial operating strategy using artificial neural network (ANN), which ensures a fault tolerance of inter-turn stator winding fault in the direct torque control (DTC) for induction motor drives. The proposed fault tolerant approach is achieved using a strategy that detects inter-turn stator winding fault, identifies fault severity and improves the DTC performance in the presence of incipient stator winding turn fault. The fault tolerant system is obtained by tuning the stator resistance to make the DTC strategy more robust and precise. This allows continuous disturbance-free operation of the induction motor drives even with existing inter-turn stator winding faults. This strategy is simple to implement, does not require new sensors or changes in the standard drive system. Experimental implementation is demonstrated for the validity of the proposed idea.

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