A look-up table-based model predictive torque control of switched reluctance motor drives with improved prediction

Diego F. Valencia; Rasul Tarvirdilu-Asl; Cristian Garcia; Jose Rodriguez; Ali Emadi

doi:10.1109/ITEC51675.2021.9490078

A look-up table-based model predictive torque control of switched reluctance motor drives with improved prediction

Diego F. Valencia, Rasul Tarvirdilu-Asl, Cristian Garcia, Jose Rodriguez, Ali Emadi

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

3 Citations (Scopus)

Abstract

This paper proposes a predictive torque control strategy based on look-up tables with improved delay compensation to enhance prediction capabilities. The tables or static maps contain the flux linkage and torque characteristics of the machine, which provides higher prediction accuracy compared to approximated analytical models. The delay compensation is enhanced by including a Kalman filter stage. The algorithm is validated through simulations and experiments using a 5.5 kW, 12/8 SRM. The results evidenced improved torque sharing capabilities with respect to conventional methods and other predictive control strategies by offering a trade-off between torque ripple production, average torque and average torque per ampere.

Original language	English
Title of host publication	2021 IEEE Transportation Electrification Conference and Expo, ITEC 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	315-320
Number of pages	6
ISBN (Electronic)	9781728175836
DOIs	https://doi.org/10.1109/ITEC51675.2021.9490078
Publication status	Published - 21 Jun 2021
Event	2021 IEEE Transportation Electrification Conference and Expo, ITEC 2021 - Chicago, United States Duration: 21 Jun 2021 → 25 Jun 2021

Publication series

Name	2021 IEEE Transportation Electrification Conference and Expo, ITEC 2021

Conference

Conference	2021 IEEE Transportation Electrification Conference and Expo, ITEC 2021
Country/Territory	United States
City	Chicago
Period	21/06/21 → 25/06/21

Keywords

Kalman filter
Model predictive control
Predictive torque control
Switched reluctance motor drive

ASJC Scopus subject areas

Automotive Engineering
Electrical and Electronic Engineering
Control and Optimization
Transportation

Access to Document

10.1109/ITEC51675.2021.9490078

Cite this

Valencia, D. F., Tarvirdilu-Asl, R., Garcia, C., Rodriguez, J., & Emadi, A. (2021). A look-up table-based model predictive torque control of switched reluctance motor drives with improved prediction. In 2021 IEEE Transportation Electrification Conference and Expo, ITEC 2021 (pp. 315-320). (2021 IEEE Transportation Electrification Conference and Expo, ITEC 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITEC51675.2021.9490078

Valencia, Diego F. ; Tarvirdilu-Asl, Rasul ; Garcia, Cristian et al. / A look-up table-based model predictive torque control of switched reluctance motor drives with improved prediction. 2021 IEEE Transportation Electrification Conference and Expo, ITEC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 315-320 (2021 IEEE Transportation Electrification Conference and Expo, ITEC 2021).

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title = "A look-up table-based model predictive torque control of switched reluctance motor drives with improved prediction",

abstract = "This paper proposes a predictive torque control strategy based on look-up tables with improved delay compensation to enhance prediction capabilities. The tables or static maps contain the flux linkage and torque characteristics of the machine, which provides higher prediction accuracy compared to approximated analytical models. The delay compensation is enhanced by including a Kalman filter stage. The algorithm is validated through simulations and experiments using a 5.5 kW, 12/8 SRM. The results evidenced improved torque sharing capabilities with respect to conventional methods and other predictive control strategies by offering a trade-off between torque ripple production, average torque and average torque per ampere. ",

keywords = "Kalman filter, Model predictive control, Predictive torque control, Switched reluctance motor drive",

author = "Valencia, {Diego F.} and Rasul Tarvirdilu-Asl and Cristian Garcia and Jose Rodriguez and Ali Emadi",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE Transportation Electrification Conference and Expo, ITEC 2021 ; Conference date: 21-06-2021 Through 25-06-2021",

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doi = "10.1109/ITEC51675.2021.9490078",

language = "English",

series = "2021 IEEE Transportation Electrification Conference and Expo, ITEC 2021",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Valencia, DF, Tarvirdilu-Asl, R, Garcia, C, Rodriguez, J & Emadi, A 2021, A look-up table-based model predictive torque control of switched reluctance motor drives with improved prediction. in 2021 IEEE Transportation Electrification Conference and Expo, ITEC 2021. 2021 IEEE Transportation Electrification Conference and Expo, ITEC 2021, Institute of Electrical and Electronics Engineers Inc., pp. 315-320, 2021 IEEE Transportation Electrification Conference and Expo, ITEC 2021, Chicago, United States, 21/06/21. https://doi.org/10.1109/ITEC51675.2021.9490078

A look-up table-based model predictive torque control of switched reluctance motor drives with improved prediction. / Valencia, Diego F.; Tarvirdilu-Asl, Rasul; Garcia, Cristian et al.
2021 IEEE Transportation Electrification Conference and Expo, ITEC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 315-320 (2021 IEEE Transportation Electrification Conference and Expo, ITEC 2021).

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

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T1 - A look-up table-based model predictive torque control of switched reluctance motor drives with improved prediction

AU - Valencia, Diego F.

AU - Tarvirdilu-Asl, Rasul

AU - Garcia, Cristian

AU - Rodriguez, Jose

AU - Emadi, Ali

PY - 2021/6/21

Y1 - 2021/6/21

N2 - This paper proposes a predictive torque control strategy based on look-up tables with improved delay compensation to enhance prediction capabilities. The tables or static maps contain the flux linkage and torque characteristics of the machine, which provides higher prediction accuracy compared to approximated analytical models. The delay compensation is enhanced by including a Kalman filter stage. The algorithm is validated through simulations and experiments using a 5.5 kW, 12/8 SRM. The results evidenced improved torque sharing capabilities with respect to conventional methods and other predictive control strategies by offering a trade-off between torque ripple production, average torque and average torque per ampere.

AB - This paper proposes a predictive torque control strategy based on look-up tables with improved delay compensation to enhance prediction capabilities. The tables or static maps contain the flux linkage and torque characteristics of the machine, which provides higher prediction accuracy compared to approximated analytical models. The delay compensation is enhanced by including a Kalman filter stage. The algorithm is validated through simulations and experiments using a 5.5 kW, 12/8 SRM. The results evidenced improved torque sharing capabilities with respect to conventional methods and other predictive control strategies by offering a trade-off between torque ripple production, average torque and average torque per ampere.

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KW - Model predictive control

KW - Predictive torque control

KW - Switched reluctance motor drive

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Valencia DF, Tarvirdilu-Asl R, Garcia C, Rodriguez J, Emadi A. A look-up table-based model predictive torque control of switched reluctance motor drives with improved prediction. In 2021 IEEE Transportation Electrification Conference and Expo, ITEC 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 315-320. (2021 IEEE Transportation Electrification Conference and Expo, ITEC 2021). doi: 10.1109/ITEC51675.2021.9490078

A look-up table-based model predictive torque control of switched reluctance motor drives with improved prediction

Abstract

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Keywords

ASJC Scopus subject areas

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