Digital Twin Service Unit Development for an EV Induction Motor Fault Detection

Viktor Rjabtsikov; Mahmoud Ibrahim; Bilal Asad; Anton Rassolkin; Toomas Vaimann; Ants Kallaste; Vladimir Kuts; Mariusz Stepien; Mateusz Krawczyk

doi:10.1109/IEMDC55163.2023.10239085

Digital Twin Service Unit Development for an EV Induction Motor Fault Detection

Viktor Rjabtsikov
, Mahmoud Ibrahim
, Bilal Asad
, Anton Rassolkin
, Toomas Vaimann
, Ants Kallaste
, Vladimir Kuts
, Mariusz Stepien
, Mateusz Krawczyk

Katedra Energoelektroniki, Napędu Elektrycznego i Robotyki (RE/RE5)

Tallinn University of Technology
Silesian University of Technology

Wyniki badań: Rozdział w książce/raport/materiał konferencyjny › Wkład w konferencję › recenzja

4 Cytowania z bazy Scopus

Abstrakt

The principle of Digital Twin (DT) is to create a connection between a physical asset and its corresponding virtual twin established by generating real-time data using sensors. DT can be used for real-time condition monitoring, fault detection, optimization, prognosis, and lifetime prediction. This paper proposes the application of a DT service unit for an electric vehicle (EV) induction motor (IM) fault detection. IM stator inter-turn short circuit fault is used as a study case to highlight the DT service unit function. Such a fault is considered one of the most prevalent possible IM failures. Based on real-time measurements, Linux Robot Operation System (ROS) simulates IM's specific behavior in case of unbalanced stator currents and notifies about possible fault appearance and propagation. The obtained results from DT allow adding additional services that consider another failure, and as a result, improve physical entity reliability.

Język oryginału	angielski
Tytuł publikacji goszczącej	2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023
Wydawca	Institute of Electrical and Electronics Engineers Inc.
ISBN (elektroniczny)	9798350398991
Identyfikatory DOI	https://doi.org/10.1109/IEMDC55163.2023.10239085
Status publikacji	Opublikowano - 2023
Wydarzenie	2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023 - San Francisco, Stany Zjednoczone Czas trwania: 15 maj 2023 → 18 maj 2023

Seria publikacji

Nazwa	2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023

Konferencja

Konferencja	2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023
Kraj/Terytorium	Stany Zjednoczone
Miejscowość	San Francisco
Okres	15/05/23 → 18/05/23

Cele SDG ONZ

Ten wynik przyczynia się do realizacji następujących celów zrównoważonego rozwoju

Cel 7 Przystępna i czysta energia

Obszary tematyczne ASJC Scopus

Inżynieria elektryczna i elektroniczna
Inżynieria mechaniczna

Uzyskaj dostęp do dokumentu

10.1109/IEMDC55163.2023.10239085

Inne pliki i linki

Link do publikacji w Scopus

Cytowanie

Rjabtsikov, V., Ibrahim, M., Asad, B., Rassolkin, A., Vaimann, T., Kallaste, A., Kuts, V., Stepien, M., & Krawczyk, M. (2023). Digital Twin Service Unit Development for an EV Induction Motor Fault Detection. W 2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023 (2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IEMDC55163.2023.10239085

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title = "Digital Twin Service Unit Development for an EV Induction Motor Fault Detection",

abstract = "The principle of Digital Twin (DT) is to create a connection between a physical asset and its corresponding virtual twin established by generating real-time data using sensors. DT can be used for real-time condition monitoring, fault detection, optimization, prognosis, and lifetime prediction. This paper proposes the application of a DT service unit for an electric vehicle (EV) induction motor (IM) fault detection. IM stator inter-turn short circuit fault is used as a study case to highlight the DT service unit function. Such a fault is considered one of the most prevalent possible IM failures. Based on real-time measurements, Linux Robot Operation System (ROS) simulates IM's specific behavior in case of unbalanced stator currents and notifies about possible fault appearance and propagation. The obtained results from DT allow adding additional services that consider another failure, and as a result, improve physical entity reliability.",

keywords = "Digital twin, fault detection, induction motor",

author = "Viktor Rjabtsikov and Mahmoud Ibrahim and Bilal Asad and Anton Rassolkin and Toomas Vaimann and Ants Kallaste and Vladimir Kuts and Mariusz Stepien and Mateusz Krawczyk",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023 ; Conference date: 15-05-2023 Through 18-05-2023",

year = "2023",

doi = "10.1109/IEMDC55163.2023.10239085",

language = "English",

series = "2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023",

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

booktitle = "2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023",

address = "United States",

}

Rjabtsikov, V, Ibrahim, M, Asad, B, Rassolkin, A, Vaimann, T, Kallaste, A, Kuts, V, Stepien, M & Krawczyk, M 2023, Digital Twin Service Unit Development for an EV Induction Motor Fault Detection. w 2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023. 2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023, Institute of Electrical and Electronics Engineers Inc., 2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023, San Francisco, Stany Zjednoczone, 15/05/23. https://doi.org/10.1109/IEMDC55163.2023.10239085

Digital Twin Service Unit Development for an EV Induction Motor Fault Detection. / Rjabtsikov, Viktor; Ibrahim, Mahmoud; Asad, Bilal i in.
2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023).

Wyniki badań: Rozdział w książce/raport/materiał konferencyjny › Wkład w konferencję › recenzja

TY - GEN

T1 - Digital Twin Service Unit Development for an EV Induction Motor Fault Detection

AU - Rjabtsikov, Viktor

AU - Ibrahim, Mahmoud

AU - Asad, Bilal

AU - Rassolkin, Anton

AU - Vaimann, Toomas

AU - Kallaste, Ants

AU - Kuts, Vladimir

AU - Stepien, Mariusz

AU - Krawczyk, Mateusz

PY - 2023

Y1 - 2023

N2 - The principle of Digital Twin (DT) is to create a connection between a physical asset and its corresponding virtual twin established by generating real-time data using sensors. DT can be used for real-time condition monitoring, fault detection, optimization, prognosis, and lifetime prediction. This paper proposes the application of a DT service unit for an electric vehicle (EV) induction motor (IM) fault detection. IM stator inter-turn short circuit fault is used as a study case to highlight the DT service unit function. Such a fault is considered one of the most prevalent possible IM failures. Based on real-time measurements, Linux Robot Operation System (ROS) simulates IM's specific behavior in case of unbalanced stator currents and notifies about possible fault appearance and propagation. The obtained results from DT allow adding additional services that consider another failure, and as a result, improve physical entity reliability.

AB - The principle of Digital Twin (DT) is to create a connection between a physical asset and its corresponding virtual twin established by generating real-time data using sensors. DT can be used for real-time condition monitoring, fault detection, optimization, prognosis, and lifetime prediction. This paper proposes the application of a DT service unit for an electric vehicle (EV) induction motor (IM) fault detection. IM stator inter-turn short circuit fault is used as a study case to highlight the DT service unit function. Such a fault is considered one of the most prevalent possible IM failures. Based on real-time measurements, Linux Robot Operation System (ROS) simulates IM's specific behavior in case of unbalanced stator currents and notifies about possible fault appearance and propagation. The obtained results from DT allow adding additional services that consider another failure, and as a result, improve physical entity reliability.

KW - Digital twin

KW - fault detection

KW - induction motor

UR - https://www.scopus.com/pages/publications/85172718564

U2 - 10.1109/IEMDC55163.2023.10239085

DO - 10.1109/IEMDC55163.2023.10239085

M3 - Conference contribution

AN - SCOPUS:85172718564

T3 - 2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023

BT - 2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023

Y2 - 15 May 2023 through 18 May 2023

ER -

Rjabtsikov V, Ibrahim M, Asad B, Rassolkin A, Vaimann T, Kallaste A i in. Digital Twin Service Unit Development for an EV Induction Motor Fault Detection. W 2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023. Institute of Electrical and Electronics Engineers Inc. 2023. (2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023). doi: 10.1109/IEMDC55163.2023.10239085

Digital Twin Service Unit Development for an EV Induction Motor Fault Detection

Abstrakt

Seria publikacji

Konferencja

Cele SDG ONZ

Obszary tematyczne ASJC Scopus

Uzyskaj dostęp do dokumentu

Inne pliki i linki

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Cytowanie