A Compact Closed-Form Dynamic Hysteresis Model for Energy-Loss Prediction in Power Magnetic Components.
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| Title: | A Compact Closed-Form Dynamic Hysteresis Model for Energy-Loss Prediction in Power Magnetic Components. |
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| Authors: | Tang, Yingjie1 (AUTHOR) ytang23@central.uh.edu, Guemri, Chayma1 (AUTHOR), Franchek, Matthew1 (AUTHOR) |
| Source: | Energies (19961073). May2026, Vol. 19 Issue 9, p2078. 18p. |
| Subject Terms: | *Energy dissipation, *Parameterization, *Magnetic cores, *Hammerstein equations, *Hysteresis loop, *Relaxation phenomena |
| Abstract: | Magnetic hysteresis strongly influences energy dissipation and efficiency in power magnetic components under time-varying excitation. This work proposes a compact dynamic hysteresis model using a Hammerstein structure, consisting of a closed-form arctangent static operator followed by a first-order relaxation dynamic stage. The formulation enables direct datasheet-based parameterization and avoids iterative differential solvers or distributed hysteron representations, resulting in low calibration effort and computational cost. The static hysteresis behavior is characterized using four static parameters directly identified from manufacturer B-H datasheets, while dynamic effects are captured using two global calibration parameters derived from datasheet loss curves. This formulation enables accurate reconstruction of major and minor hysteresis loops, while introducing frequency-dependent phase lag and dynamic loop opening. Model performance is evaluated under diverse excitations, including sinusoidal, amplitude-modulated, FORC and chirp signals, showing waveform deviations below 7.2% peak-to-peak NRMSE relative to classical hysteresis models. Energy-loss predictions are validated against manufacturer datasheet curves for ferrite material 3C90 across multiple frequencies, yielding a root-mean-square relative error of 8.3% with 89% of operating points within ±20% deviation. The proposed model provides a datasheet-driven framework for hysteresis and energy-loss prediction in power magnetic components. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: enr DbLabel: Energy & Power Source An: 193715974 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A Compact Closed-Form Dynamic Hysteresis Model for Energy-Loss Prediction in Power Magnetic Components. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Tang%2C+Yingjie%22">Tang, Yingjie</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> ytang23@central.uh.edu</i><br /><searchLink fieldCode="AR" term="%22Guemri%2C+Chayma%22">Guemri, Chayma</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Franchek%2C+Matthew%22">Franchek, Matthew</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. May2026, Vol. 19 Issue 9, p2078. 18p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Energy+dissipation%22">Energy dissipation</searchLink><br />*<searchLink fieldCode="DE" term="%22Parameterization%22">Parameterization</searchLink><br />*<searchLink fieldCode="DE" term="%22Magnetic+cores%22">Magnetic cores</searchLink><br />*<searchLink fieldCode="DE" term="%22Hammerstein+equations%22">Hammerstein equations</searchLink><br />*<searchLink fieldCode="DE" term="%22Hysteresis+loop%22">Hysteresis loop</searchLink><br />*<searchLink fieldCode="DE" term="%22Relaxation+phenomena%22">Relaxation phenomena</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Magnetic hysteresis strongly influences energy dissipation and efficiency in power magnetic components under time-varying excitation. This work proposes a compact dynamic hysteresis model using a Hammerstein structure, consisting of a closed-form arctangent static operator followed by a first-order relaxation dynamic stage. The formulation enables direct datasheet-based parameterization and avoids iterative differential solvers or distributed hysteron representations, resulting in low calibration effort and computational cost. The static hysteresis behavior is characterized using four static parameters directly identified from manufacturer B-H datasheets, while dynamic effects are captured using two global calibration parameters derived from datasheet loss curves. This formulation enables accurate reconstruction of major and minor hysteresis loops, while introducing frequency-dependent phase lag and dynamic loop opening. Model performance is evaluated under diverse excitations, including sinusoidal, amplitude-modulated, FORC and chirp signals, showing waveform deviations below 7.2% peak-to-peak NRMSE relative to classical hysteresis models. Energy-loss predictions are validated against manufacturer datasheet curves for ferrite material 3C90 across multiple frequencies, yielding a root-mean-square relative error of 8.3% with 89% of operating points within ±20% deviation. The proposed model provides a datasheet-driven framework for hysteresis and energy-loss prediction in power magnetic components. [ABSTRACT FROM AUTHOR] |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=enr&AN=193715974 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/en19092078 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 18 StartPage: 2078 Subjects: – SubjectFull: Energy dissipation Type: general – SubjectFull: Parameterization Type: general – SubjectFull: Magnetic cores Type: general – SubjectFull: Hammerstein equations Type: general – SubjectFull: Hysteresis loop Type: general – SubjectFull: Relaxation phenomena Type: general Titles: – TitleFull: A Compact Closed-Form Dynamic Hysteresis Model for Energy-Loss Prediction in Power Magnetic Components. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Tang, Yingjie – PersonEntity: Name: NameFull: Guemri, Chayma – PersonEntity: Name: NameFull: Franchek, Matthew IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: May2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 19961073 Numbering: – Type: volume Value: 19 – Type: issue Value: 9 Titles: – TitleFull: Energies (19961073) Type: main |
| ResultId | 1 |
