Experimental Assessment of Weighting-Factorless Predictive Current Control for Asymmetrical Six-Phase Induction Motor

Mohamed Mamdouh; Ayman Samy Abdel-Khalik; Mohamed Ali Abido

doi:10.1109/IECON49645.2022.9968365

Experimental Assessment of Weighting-Factorless Predictive Current Control for Asymmetrical Six-Phase Induction Motor

Mohamed Mamdouh, Ayman Samy Abdel-Khalik, Mohamed Ali Abido

Department of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

The weighting factor (WF) setting is one of the most challenging tasks related to finite control set model predictive control (FCS-MPC) algorithms in different applications. Recently, a new method has been proposed for weighting factor elimination (WFE) in predictive current control (PCC) of asymmetric six-phase induction motor (A6PIM). This method is based on adopting the double dq (2dq) modeling method for prediction and optimization steps. As a result, the proposed cost function consists of four stator current components with the same priority. Thus, equal weighting factors can be assumed. In this paper, the performance of WFE method is assessed experimentally at different operating conditions. Different figures of merit are used to further compare it with the conventional voltage space decomposition (VSD)-based method. The WFE method is found to have reduced average switching frequency and better current quality. By highlighting the potential and limitations of WFE method it can be used properly based on different applications requirements.

Original language	English
Title of host publication	IECON 2022 - 48th Annual Conference of the IEEE Industrial Electronics Society
Publisher	IEEE Computer Society
ISBN (Electronic)	9781665480253
DOIs	https://doi.org/10.1109/IECON49645.2022.9968365
State	Published - 2022
Event	48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022 - Brussels, Belgium Duration: 17 Oct 2022 → 20 Oct 2022

Publication series

Name	IECON Proceedings (Industrial Electronics Conference)
Volume	2022-October
ISSN (Print)	2162-4704
ISSN (Electronic)	2577-1647

Conference

Conference	48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022
Country/Territory	Belgium
City	Brussels
Period	17/10/22 → 20/10/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

predictive current control
six-phase induction motor
weighting factor elimination

ASJC Scopus subject areas

Control and Systems Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/IECON49645.2022.9968365

Cite this

Mamdouh, M., Abdel-Khalik, A. S., & Ali Abido, M. (2022). Experimental Assessment of Weighting-Factorless Predictive Current Control for Asymmetrical Six-Phase Induction Motor. In IECON 2022 - 48th Annual Conference of the IEEE Industrial Electronics Society (IECON Proceedings (Industrial Electronics Conference); Vol. 2022-October). IEEE Computer Society. https://doi.org/10.1109/IECON49645.2022.9968365

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title = "Experimental Assessment of Weighting-Factorless Predictive Current Control for Asymmetrical Six-Phase Induction Motor",

abstract = "The weighting factor (WF) setting is one of the most challenging tasks related to finite control set model predictive control (FCS-MPC) algorithms in different applications. Recently, a new method has been proposed for weighting factor elimination (WFE) in predictive current control (PCC) of asymmetric six-phase induction motor (A6PIM). This method is based on adopting the double dq (2dq) modeling method for prediction and optimization steps. As a result, the proposed cost function consists of four stator current components with the same priority. Thus, equal weighting factors can be assumed. In this paper, the performance of WFE method is assessed experimentally at different operating conditions. Different figures of merit are used to further compare it with the conventional voltage space decomposition (VSD)-based method. The WFE method is found to have reduced average switching frequency and better current quality. By highlighting the potential and limitations of WFE method it can be used properly based on different applications requirements.",

keywords = "predictive current control, six-phase induction motor, weighting factor elimination",

author = "Mohamed Mamdouh and Abdel-Khalik, \{Ayman Samy\} and \{Ali Abido\}, Mohamed",

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doi = "10.1109/IECON49645.2022.9968365",

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Mamdouh, M, Abdel-Khalik, AS & Ali Abido, M 2022, Experimental Assessment of Weighting-Factorless Predictive Current Control for Asymmetrical Six-Phase Induction Motor. in IECON 2022 - 48th Annual Conference of the IEEE Industrial Electronics Society. IECON Proceedings (Industrial Electronics Conference), vol. 2022-October, IEEE Computer Society, 48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022, Brussels, Belgium, 17/10/22. https://doi.org/10.1109/IECON49645.2022.9968365

Experimental Assessment of Weighting-Factorless Predictive Current Control for Asymmetrical Six-Phase Induction Motor. / Mamdouh, Mohamed; Abdel-Khalik, Ayman Samy; Ali Abido, Mohamed.
IECON 2022 - 48th Annual Conference of the IEEE Industrial Electronics Society. IEEE Computer Society, 2022. (IECON Proceedings (Industrial Electronics Conference); Vol. 2022-October).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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PY - 2022

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N2 - The weighting factor (WF) setting is one of the most challenging tasks related to finite control set model predictive control (FCS-MPC) algorithms in different applications. Recently, a new method has been proposed for weighting factor elimination (WFE) in predictive current control (PCC) of asymmetric six-phase induction motor (A6PIM). This method is based on adopting the double dq (2dq) modeling method for prediction and optimization steps. As a result, the proposed cost function consists of four stator current components with the same priority. Thus, equal weighting factors can be assumed. In this paper, the performance of WFE method is assessed experimentally at different operating conditions. Different figures of merit are used to further compare it with the conventional voltage space decomposition (VSD)-based method. The WFE method is found to have reduced average switching frequency and better current quality. By highlighting the potential and limitations of WFE method it can be used properly based on different applications requirements.

AB - The weighting factor (WF) setting is one of the most challenging tasks related to finite control set model predictive control (FCS-MPC) algorithms in different applications. Recently, a new method has been proposed for weighting factor elimination (WFE) in predictive current control (PCC) of asymmetric six-phase induction motor (A6PIM). This method is based on adopting the double dq (2dq) modeling method for prediction and optimization steps. As a result, the proposed cost function consists of four stator current components with the same priority. Thus, equal weighting factors can be assumed. In this paper, the performance of WFE method is assessed experimentally at different operating conditions. Different figures of merit are used to further compare it with the conventional voltage space decomposition (VSD)-based method. The WFE method is found to have reduced average switching frequency and better current quality. By highlighting the potential and limitations of WFE method it can be used properly based on different applications requirements.

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Experimental Assessment of Weighting-Factorless Predictive Current Control for Asymmetrical Six-Phase Induction Motor

Abstract

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Keywords

ASJC Scopus subject areas

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