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Design and Experimental Validation of a Multiphysics Twin of a High Voltage EV Motor
  • +8
  • Riccardo Torchio ,
  • F Conte,
  • A Martin,
  • N Bianchi,
  • M De Soricellis,
  • F Toso,
  • F Pase,
  • M Scarpa,
  • M Filippini,
  • M Lurtz,
  • D Szepanski
Riccardo Torchio
Department of Information Engineering, University of Padova, Department of Industrial Engi-neering, University of Padova

Corresponding Author:[email protected]

Author Profile
F Conte
Department of Industrial Engi-neering, University of Padova
A Martin
N Bianchi
Department of Industrial Engi-neering, University of Padova
M De Soricellis
F Toso
F Pase
M Scarpa
Department of Information Engineering, University of Padova, Department of Information Engineering, Univer-sity of Padova
M Filippini
M Lurtz
D Szepanski

Abstract

The integration of electric motors into various industrial and automotive applications emphasizes the critical necessity for reliable performance and operational efficiency. The advent of advanced digital technologies offers opportunities for predictive maintenance strategies. Digital Twins (DTs), mathematical models simulating a system's physical behavior in real-time, present a transformative approach to enhance real-time monitoring of critical quantities, which is imperative to improve operational efficiency and minimize downtime. In this paper, we explore the feasibility and efficacy of deploying real-time physics-based DTs for condition monitoring in electric motor applications. Particularly, we focus on employing on-the-edge DTs, implemented on low-power onboard microprocessors, ensuring continuous communication with the physical asset for reliable real-time monitoring. The study applies DT technology to a high-voltage high-density Electric Vehicle (EV) motor, assessing its predictive capabilities in a real-world scenario. Results showcase the potential of DTs in revolutionizing condition monitoring, thereby meeting the evolving operational and maintenance requirements of contemporary electric motor systems.
16 Mar 2024Submitted to TechRxiv
29 Mar 2024Published in TechRxiv