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.