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Stability of Jiles-Atherton Anhysteretic Magnetization Curve Model for Magnetic Materials with Uniaxial Anisotropy | SpringerLink
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Stability of Jiles-Atherton Anhysteretic Magnetization Curve Model for Magnetic Materials with Uniaxial Anisotropy

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Automation 2020: Towards Industry of the Future (AUTOMATION 2020)

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Abstract

Anhysteretic magnetization curve plays the key role in modelling the characteristics of components made of soft magnetic materials. However, due to the positive feedback, for some set of parameters the most common model of magnetization curve might be unstable. Moreover, formal stability assessment of anhysteretic magnetization curve is sophisticated due to nonlinearities. Paper presents practical approach to stability assessment of Jiles-Atherton anhysteretic magnetization curve model for magnetic materials with uniaxial anisotropy. Results of this assessment enable the increase of efficiency of the process of identification of the model’s parameters, and as a result enable more efficient description of functional characteristics of inductive components with cores made of anisotropic soft magnetic materials.

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Authors and Affiliations

  1. ŁUKASIEWICZ Research Network – Industrial Research Institute for Automation and Measurements PIAP, Al. Jerozolimskie 202, 02-486, Warsaw, Poland

    Roman Szewczyk

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  1. Roman Szewczyk
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Correspondence to Roman Szewczyk .

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Editors and Affiliations

  1. ŁUKASIEWICZ Research Network, Industrial Research Institute for Automation and Measurements PIAP, Warsaw, Poland

    Roman Szewczyk

  2. ŁUKASIEWICZ Research Network, Industrial Research Institute for Automation and Measurements PIAP, Warsaw, Poland

    Cezary Zieliński

  3. ŁUKASIEWICZ Research Network, Industrial Research Institute for Automation and Measurements PIAP, Warsaw, Poland

    Małgorzata Kaliczyńska

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Szewczyk, R. (2020). Stability of Jiles-Atherton Anhysteretic Magnetization Curve Model for Magnetic Materials with Uniaxial Anisotropy. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds) Automation 2020: Towards Industry of the Future. AUTOMATION 2020. Advances in Intelligent Systems and Computing, vol 1140. Springer, Cham. https://doi.org/10.1007/978-3-030-40971-5_32

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