Accuracy of Core Losses Estimation in PMSM: A Comparison of Empirical and Numerical Approximation Models

Michael Nye, Matilde D’Arpino () and Luigi Pio Di Noia
Additional contact information
Michael Nye: Department of Electrical and Computer Engineering, The Ohio State University, Columbus, OH 43210, USA
Matilde D’Arpino: Department of Electrical and Computer Engineering, The Ohio State University, Columbus, OH 43210, USA
Luigi Pio Di Noia: Department of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Naples, Italy

Energies, 2025, vol. 18, issue 17, 1-19

Abstract: The estimation of core loss in permanent magnet synchronous machines (PMSMs) is a fundamental step for the optimization of the performance of PMSM drives. However, there is a lack of literature which fully demonstrates the goodness of some of the empirical approximations that are commonly used in industrial and automotive sectors. This work investigates how different approximations for the core loss estimation of PMSMs can lead to considerable error across the entire machine operating domain. An interior PMSM (IPMSM) is modeled in finite element analysis (FEA) and used to calibrate the coefficients of the Bertotti equation. Approximations of the Bertotti equation are then made, which are calculated from a simple algebraic expression of measurable states, and these are used to estimate machine core loss in the whole direct-quadrature ( d − q ) domain of operation. The estimated core loss obtained with the approximations are finally compared to FEA core loss results. The approximations are shown to have considerable variability in their accuracy compared to FEA results. The results of this work can be used as guidance during the development of estimation algorithms for PMSM losses and the development of control strategies.

Keywords: electric machine; permanent magnet; core loss; modeling; FEA (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
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/18/17/4494/pdf (application/pdf)
https://www.mdpi.com/1996-1073/18/17/4494/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:18:y:2025:i:17:p:4494-:d:1731245

Access Statistics for this article

Energies is currently edited by Ms. Cassie Shen

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().