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

Department of Power Electronics, Electrical Drives and Robotics (RE/RE5)

Tallinn University of Technology
Silesian University of Technology

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

4 Citations (Scopus)

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.

Original language	English
Title of host publication	2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350398991
DOIs	https://doi.org/10.1109/IEMDC55163.2023.10239085
Publication status	Published - 2023
Event	2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023 - San Francisco, United States Duration: 15 May 2023 → 18 May 2023

Publication series

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

Conference

Conference	2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023
Country/Territory	United States
City	San Francisco
Period	15/05/23 → 18/05/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Digital twin
fault detection
induction motor

ASJC Scopus subject areas

Electrical and Electronic Engineering
Mechanical Engineering

Access to Document

10.1109/IEMDC55163.2023.10239085

Cite this

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. In 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",

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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. in 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, United States, 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 et al.
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).

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

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

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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.

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Y2 - 15 May 2023 through 18 May 2023

ER -

Rjabtsikov V, Ibrahim M, Asad B, Rassolkin A, Vaimann T, Kallaste A et al. Digital Twin Service Unit Development for an EV Induction Motor Fault Detection. 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). doi: 10.1109/IEMDC55163.2023.10239085

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

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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