A direct search algorithm for estimation of Jiles–Atherton hysteresis model parameters

Chwastek, Krzysztof; Szczygłowski, J.; Najgebauer, Mariusz

doi:10.1016/j.mseb.2005.11.030

Cited by 16 publications

(12 citation statements)

References 15 publications

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“…Also, by increasing the excitation frequency, eddy currents increase, which generates magnetic fields reacting to the external field. Therefore, the Hc value tends to increase with frequency, since the applied magnetic field is high enough for the magnetic saturation be attained, as discussed by Szczyglowski [36] and Chwastek et al [37]. However, if the applied field is not sufficient for the magnetic saturation, this trend may not be observed.…”

Section: Resultsmentioning

confidence: 86%

Relation Between Magnetic Barkhausen Noise and Hardness for Jominy Quench Tests in SAE 4140 and 6150 Steels

et al. 2012

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Microstructures were also characterized by SEM (Scanning Electron Microscope) and hardness tests. MBN measurements were performed on the same sample regions at three excitation frequencies. Different parameters of the measured signals (signal peak position and height, and Root mean square) were calculated. A relationship between mechanical hardness and MBN parameters was found for both materials, with the best correlation coefficient being found in low excitation frequency range.

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Section: Resultsmentioning

confidence: 86%

Relation Between Magnetic Barkhausen Noise and Hardness for Jominy Quench Tests in SAE 4140 and 6150 Steels

et al. 2012

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“…The fourth model (further called the “ Langevin function-based model ”) utilizes the Langevin equation, commonly used for modeling the magnetization curve of paramagnetic materials. Previously, it has commonly been used for modeling the anhysteretic curve of different materials in the Jiles-Atherton model [17,18,19,20]. The Langevin function-based model is given by the following equation [2]:M(H)=Ms·(coth(Hea)−aHe) which is determined by the Boltzman distribution of magnetic moments [21].…”

Section: Models Of Anhysteretic Curvementioning

confidence: 99%

Experimental Verification of Isotropic and Anisotropic Anhysteretic Magnetization Models

2019

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The anhysteretic magnetization curve is the key element of modeling magnetic hysteresis loops. Despite the fact that it is intensively exploited, known models of anhysteretic curve have not been verified experimentally. This paper presents the validation of four anhysteretic curve models considering four different materials, including isotropic, such as Mn-Zn soft ferrite, as well as anisotropic amorphous and nanocrystalline alloys. The presented results indicate that only the model that considers anisotropic energy is valid for a wide set of modern magnetic materials. The most suitable of the verified models is the anisotropic extension function-based model, which considers uniaxial anisotropy.

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“…JA model in the form of a set of nonlinear and first-order ordinary differential equations has five parameters with a clear physical interpretation, which is difficult to be determined. In order to solve the estimation problems of JA model, some researchers have implemented several methods in recent years, such as DE [2], GA [3] and PSO [4], but the results are not satisfactory. A new FuzzyShuffled Frog Leaping Algorithm (F-SFLA) is proposed in this paper to calculate the JA model parameters.…”

Section: Introductionmentioning

confidence: 99%

Determination of JA core hysteresis model parameters based on fuzzy-shuffled frog leaping algorithm

Wang

Liu

2015

2015 IEEE International Conference on Applied Superconductivity and Electromagnetic Devices (ASEMD)

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Jiles Atherton (JA) model is widely used in transformer core hysteresis field. The expression of iron core hysteresis phenomenon is affected by the accuracy of its parameters. This paper proposes a Fuzzy-Shuffled Frog Leaping Algorithm to determine the JA model parameters. To improve the convergence speed of algorithm and restrain the unphysical results, the range of JA model parameters is determined. The fuzzy logic is used to overcome the shortage of Shuffled Frog Leaping Algorithm without feedback. The calculated results compared with the core hysteresis loop measured by Epstein frame show the effectiveness of the method. Keywords-JA core hysteresis model; range of JA model parameters; Fuzzy-Shuffled Frog Leaping Algorithm; Epstein frame measuring system

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A direct search algorithm for estimation of Jiles–Atherton hysteresis model parameters

Cited by 16 publications

References 15 publications

Relation Between Magnetic Barkhausen Noise and Hardness for Jominy Quench Tests in SAE 4140 and 6150 Steels

Relation Between Magnetic Barkhausen Noise and Hardness for Jominy Quench Tests in SAE 4140 and 6150 Steels

Experimental Verification of Isotropic and Anisotropic Anhysteretic Magnetization Models

Determination of JA core hysteresis model parameters based on fuzzy-shuffled frog leaping algorithm

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