AI Enabled Digital Twin of the Traction Motor of an Electric Vehicle

<div class="section abstract"><div class="htmlview paragraph">Electric motors are critical components in Electric Vehicle (EV) & industrial applications. In case of EVs electric motor has a direct impact on the functionality, range and general user experience. Traditional maintenance procedures have several major limitations such as, leaving no choice but to use the expensive warranty claims, restricted predictive maintenance, unavailability of useful data, reducing resale value, and ultimately poor customer satisfaction. The process of building a virtual duplicate of an actual motor that can replicate the physical system in real time is known as the Digital Twin (DT) technology. Here, the DT technology-based monitoring and maintenance is initiated on permanent magnet synchronous motor (PMSM) used in traction, thus helping to overcome the drawbacks of traditional maintenance system. To provide a holistic approach to real time motor monitoring, motor management, ensuring enhanced reliability, efficiency, and predictive maintenance capabilities, the solution includes an intuitive real-time monitoring interface, digital models based on mathematics and artificial intelligence (AI), anomaly detection, and GenAI-based motor failure identification. The developed motor Digital Twin improves the motor reliability, efficiency, reduce cost of maintenance and other related cost and can also serve as future scope to data repository and provide as “DT as a Service”.</div></div>