View in EDS PDF Full Text

Time-Domain Iron Loss Estimation Using the Parametric Magneto Dynamic Model: Discretisation Sensitivity and a Skin-Depth-Based Heuristic.

Saved in:
Bibliographic Details
Title: Time-Domain Iron Loss Estimation Using the Parametric Magneto Dynamic Model: Discretisation Sensitivity and a Skin-Depth-Based Heuristic.
Authors: Hörmann, Timo1 timo.hoermann@iem.rwth-aachen.de, Rahmanovic, Ermin2 ermin.rahmanovic@um.si, Aurich, Danilo Gartner1 danilo.aurich@iem.rwth-aachen.de, Petrun, Martin2 martin.petrun@um.si, Steentjes, Simon1 simon.steentjes@iem.rwth-aachen.de
Source: Serbian Journal of Electrical Engineering. Jun2026, Vol. 23 Issue 2, p183-202. 20p.
Subjects: Discretization methods, Magnetic hysteresis, Steel alloys, Magnetization, Time-domain analysis, Heuristic
Abstract: This paper utilizes the Parametric Magneto-Dynamic (PMD) model, enhanced with an inverse hysteresis formulation, to estimate iron losses in the time domain under arbitrary excitation waveforms. The proposed PMD model reproduces the intricate magnetization dynamics of advanced steel grades, facilitating a systematic investigation into how metallurgical and geometric material properties - such as lamination thickness, alloy composition, and grain morphology - influence the required spatial and temporal discretisation for accurate loss estimation. The paper evaluates the consequences of discretisation parameters in the PMD model on both the accuracy of the iron loss prediction accuracy and computational overhead. The findings establish rigorous guidelines on the required discretisation schemes for purely sinusoidal excitation and for nonsinusoidal regimes with significant harmonic content across a broad frequency spectrum. [ABSTRACT FROM AUTHOR]
Copyright of Serbian Journal of Electrical Engineering is the property of Serbian Journal of Electrical Engineering and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Links:
  – Type: pdflink
Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 195752611
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Time-Domain Iron Loss Estimation Using the Parametric Magneto Dynamic Model: Discretisation Sensitivity and a Skin-Depth-Based Heuristic.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Hörmann%2C+Timo%22">Hörmann, Timo</searchLink><relatesTo>1</relatesTo><i> timo.hoermann@iem.rwth-aachen.de</i><br /><searchLink fieldCode="AR" term="%22Rahmanovic%2C+Ermin%22">Rahmanovic, Ermin</searchLink><relatesTo>2</relatesTo><i> ermin.rahmanovic@um.si</i><br /><searchLink fieldCode="AR" term="%22Aurich%2C+Danilo+Gartner%22">Aurich, Danilo Gartner</searchLink><relatesTo>1</relatesTo><i> danilo.aurich@iem.rwth-aachen.de</i><br /><searchLink fieldCode="AR" term="%22Petrun%2C+Martin%22">Petrun, Martin</searchLink><relatesTo>2</relatesTo><i> martin.petrun@um.si</i><br /><searchLink fieldCode="AR" term="%22Steentjes%2C+Simon%22">Steentjes, Simon</searchLink><relatesTo>1</relatesTo><i> simon.steentjes@iem.rwth-aachen.de</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Serbian+Journal+of+Electrical+Engineering%22">Serbian Journal of Electrical Engineering</searchLink>. Jun2026, Vol. 23 Issue 2, p183-202. 20p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Discretization+methods%22">Discretization methods</searchLink><br /><searchLink fieldCode="DE" term="%22Magnetic+hysteresis%22">Magnetic hysteresis</searchLink><br /><searchLink fieldCode="DE" term="%22Steel+alloys%22">Steel alloys</searchLink><br /><searchLink fieldCode="DE" term="%22Magnetization%22">Magnetization</searchLink><br /><searchLink fieldCode="DE" term="%22Time-domain+analysis%22">Time-domain analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Heuristic%22">Heuristic</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This paper utilizes the Parametric Magneto-Dynamic (PMD) model, enhanced with an inverse hysteresis formulation, to estimate iron losses in the time domain under arbitrary excitation waveforms. The proposed PMD model reproduces the intricate magnetization dynamics of advanced steel grades, facilitating a systematic investigation into how metallurgical and geometric material properties - such as lamination thickness, alloy composition, and grain morphology - influence the required spatial and temporal discretisation for accurate loss estimation. The paper evaluates the consequences of discretisation parameters in the PMD model on both the accuracy of the iron loss prediction accuracy and computational overhead. The findings establish rigorous guidelines on the required discretisation schemes for purely sinusoidal excitation and for nonsinusoidal regimes with significant harmonic content across a broad frequency spectrum. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Serbian Journal of Electrical Engineering is the property of Serbian Journal of Electrical Engineering and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=195752611
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.2298/SJEE2602183H
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 20
        StartPage: 183
    Subjects:
      – SubjectFull: Discretization methods
        Type: general
      – SubjectFull: Magnetic hysteresis
        Type: general
      – SubjectFull: Steel alloys
        Type: general
      – SubjectFull: Magnetization
        Type: general
      – SubjectFull: Time-domain analysis
        Type: general
      – SubjectFull: Heuristic
        Type: general
    Titles:
      – TitleFull: Time-Domain Iron Loss Estimation Using the Parametric Magneto Dynamic Model: Discretisation Sensitivity and a Skin-Depth-Based Heuristic.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Hörmann, Timo
      – PersonEntity:
          Name:
            NameFull: Rahmanovic, Ermin
      – PersonEntity:
          Name:
            NameFull: Aurich, Danilo Gartner
      – PersonEntity:
          Name:
            NameFull: Petrun, Martin
      – PersonEntity:
          Name:
            NameFull: Steentjes, Simon
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 06
              Text: Jun2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 14514869
          Numbering:
            – Type: volume
              Value: 23
            – Type: issue
              Value: 2
          Titles:
            – TitleFull: Serbian Journal of Electrical Engineering
              Type: main
ResultId 1