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\title{Design and Experimental Validation of a Multiphysics Twin of a High Voltage EV Motor}



\author[1,2]{Riccardo Torchio}%
\author[2]{F Conte}%
\author[3]{A Martin}%
\author[2]{N Bianchi}%
\author[3]{M De Soricellis}%
\author[3]{F Toso}%
\author[3]{F Pase}%
\author[1,4]{M Scarpa}%
\author[3]{M Filippini}%
\author[3]{M Lurtz}%
\author[3]{D Szepanski}%
\affil[1]{Department of Information Engineering, University of Padova}%
\affil[2]{Department of Industrial Engi-neering, University of Padova}%
\affil[3]{Affiliation not available}%
\affil[4]{Department of Information Engineering, Univer-sity of Padova}%


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  \date{April 30, 2026}


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\begin{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.%
\end{abstract}%



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CITE THIS PAPER AS:~

R. Torchio~\emph{et al}., ``Design and Experimental Validation of a
Multiphysics Twin of a High Voltage EV Motor,'' in~\emph{IEEE
Transactions on Transportation Electrification}, doi:
10.1109/TTE.2024.3437475.

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