Towards Digital Twin Modeling and Applications for Permanent Magnet Synchronous Motors

Grace Firsta Lukman and Cheewoo Lee ()
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Grace Firsta Lukman: Department of Electrical and Electronics Engineering, Pusan National University, Busan 46241, Republic of Korea
Cheewoo Lee: Department of Electrical and Electronics Engineering, Pusan National University, Busan 46241, Republic of Korea

Energies, 2025, vol. 18, issue 4, 1-24

Abstract: This paper explores the potential of Digital Twin (DT) technology for Permanent Magnet Synchronous Motors (PMSMs) and establishes a foundation for its modeling and applications. While DTs have been widely applied in complex systems and simulation software, their use in electric motors, especially PMSMs, remains limited. This study examines physics-based, data-driven, and hybrid modeling approaches and evaluates their feasibility for real-time simulation, fault detection, and predictive maintenance. It also identifies key challenges such as computational demands, data integration, and the lack of standardized frameworks. By assessing current developments and outlining future directions, this work provides insights into how DTs can be implemented for PMSMs and drive advancements in industrial applications.

Keywords: digital twin; Permanent Magnet Synchronous Motors; machine learning; prospective application; IoT integration (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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