Modeling and Parameter Identification Methods for Static Energetic Hysteresis Permeance Model and Effectiveness Evaluation Article Swipe

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YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.1002/tee.70206

A transformer model that considers the hysteresis effect of the iron core is crucial for accurately simulating electromagnetic transient processes such as DC bias, inrush current, and short‐circuit faults in transformers. The core hysteresis permeance model based on the permeance‐capacitance analogy is suitable for transformer simulation due to its reasonable energy analogy and strong electromagnetic information representation. However, framework structures and solution methods vary with different hysteresis models, affecting simulation accuracy. This paper comprehensively evaluates three hysteresis permeance models. First, the modeling process via permeance‐capacitance analogy is summarized. Building upon existing Preisach and Jiles‐Atherton (J‐A) models, a static Energetic hysteresis permeance model is established to better reflect microscopic magnetization characteristics. Then, comparative analyses are conducted regarding parameter identification difficulty, parameter quantity, and hysteresis loop accuracy for different core materials. Finally, fixed‐step and variable‐step algorithms are employed to evaluate solution data distribution, computational efficiency, and simulation stability over multiple cycles. The simulation discrepancies are systematically analyzed considering inherent characteristics of each hysteresis model. © 2025 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

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Type: article
Language: en
Landing Page: https://doi.org/10.1002/tee.70206
PDF: https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/tee.70206
OA Status: bronze
References: 8
OpenAlex ID: https://openalex.org/W4415724304

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OpenAlex ID: https://openalex.org/W4415724304

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DOI: https://doi.org/10.1002/tee.70206

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Title: Modeling and Parameter Identification Methods for Static Energetic Hysteresis Permeance Model and Effectiveness Evaluation

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Type: article

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Language: en

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Publication year: 2025

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Publication date: 2025-10-31

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Authors: Bin Chen, Ming Zhang, Yibo Chen

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Landing page: https://doi.org/10.1002/tee.70206

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PDF URL: https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/tee.70206

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OA status: bronze

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OA URL: https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/tee.70206

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Cited by: 0

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References (count): 8

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