Models of Hysteresis in Magnetic Cores

IEEE Transactions on Magnetics, 1989

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IEEE Transactions on Instrumentation and Measurement, 1994

Many methods have been proposed for the determination of the hysteresis loops of magnetic materials, and many mathematical approaches have been proposed to find a good model for the hysteresis phenomenon. However, very few attempts have been made to determine the parameters of the hysteresis model experimentally. This paper will show how, starting from a digital method for the experimental determination of the hysteresis loop under different maximum induction values, the parameters of a hysteresis model can be automatically estimated with good accuracy.

IEEE Transactions on Electromagnetic Compatibility, 2015

This paper proposes a numerical solution of the nonlinear equations that describes the hysteretic behavior of ferromagnetic materials. From the proper definition and solution of these equations, an equivalent circuit model for a ferromagnetic core is developed and proposed. The results obtained from the equivalent circuit are compared with those obtained by a rigorous numerical solution.

Journal of Applied Physics, 1983

We have obtained theoretical expressions for the ferromagnetic magnetization curve and hysteresis loop using an extension of the general ideas of the Globus model for polycrystalline ferrimagnets. In this work we take into account the force which resul ts from the variation of the total energy (magnetic energy plus surface energy) in order to find the value of the critical field . Our theoretical magnetization curve agrees well with the experimental curve and our hysteresis loop has the general qualitative features of the corresponding experimental loops.

Journal of Materials Processing Technology, 2007

This paper presents a method based on use of a measurement system in order to significantly reduce the time taken and to improve the accuracy in evaluating parameters of the Jiles-Atherton's model of magnetic hysteresis. The steps of the proposed method: (a) data acquisition from the experimental hysteresis loop of the magnetic material under test, (b) evaluation of the model's parameters. In order to highlight the method's effectiveness, the results of experimental tests are also given.

Le Journal de Physique IV, 1998

In this paper. the first magnetisation response experilncnrally ohscrvcd on 0.5 nim lliick slicerh ~liadc 01.3 non-oriented silicon-iron alloy is given for different magnetic loading frcqucncies from 0.05 to 500 H I. An internal variable magnetic hysteresis model is identified from the quasi-static rehponse (from 0.05 to ahout 5 H I). This modcl is used for finite clement analyses performed to predict the elccrro-niagnctic response of the nlnrcrial at higher frequencies. The colnparison between the results of ~Iicse structur;ll analyses ;~nd the expcri~iicntal results proves t1i;lt in this case [he macroscopic cddy currenls arc suff~cicnt ~o explain the tot;~l l'requcncy cl'fccl 11n ~h c mognctic hysteresis measurements.

Bulletin of the American Physical …, 2013

Ferromagnetic materials occur in single or multi-phase state and furthermore can undergo phase changes during processing or over time during service exposure. These phase changes can be attributed to physical processes or chemical reactions. In this paper, we examine the hysteresis and Barkhausen emission profiles of two-phase magnetic materials. Besides the shape of magnetic hysteresis curves that can reveal the presence of more than one phase, we demonstrate that the Barkhausen noise signatures for two-phase materials form two-peaks in their Barkhausen voltage profile. This can be used as a tool for non-destructive evaluation of ferromagnetic materials in industrial applications.

Journal of Microwaves, Optoelectronics and Electromagnetic Applications

The Jiles-Atherton scalar hysteresis model presents five parameters used to represent the material tested and used to calculate the magnetic losses. This article presents a comparative analysis of the performance of two methods of identifying these parameters. In the first method, the equations of Jiles-Atherton were assembled into a single non-linear ordinary differential equation as a function of the variables of interest. An algebraic system of five equations with five unknowns is obtained by evaluating the non-linear ordinary differential equation in five points belonging to the branch of the experimental hysteresis loop. The parameters are obtained by solving this system of equations using the method of Non-Linear Least Squares (NLLS). In the second method, the inverse model of Jiles-Atherton is used to calculate the magnetic field H from the experimental values of magnetic induction B. Using the method of genetic algorithms (MGA), the objective function given by the sum of the relative error of calculated magnetic field and experimental magnetic field along the hysteresis loop is minimized. To validate methods the experimental curves were compared with calculated ones. When applying the methods, it was verified that NLLS besides providing more accurate results, it is faster when compared to MGA. In the MGA the convergence of the calculated magnitudes to the experimental magnitudes improves when one of the chromosomes of the initial population is the solution obtained applying NLLS.

Archives of Electrical Engineering, 2012

Thermal effects on magnetic hysteresis modelingA temperature dependent model is necessary for the generation of hysteresis loops of ferromagnetic materials. In this study, a physical model based on the Jiles-Atherton model has been developed to study the effect of temperature on the magnetic hysteresis loop. The thermal effects were included through a model of behavior depending on the temperature parametersMsandkof the Jiles-Atherton model. The temperature-dependent Jiles-Atherton model was validated through measurements made on ferrite material (3F3). The results have been found to be in good agreement with the model.

Magnetochemistry, 2021

A thorough investigation of the 2-D hysteresis processes under arbitrary excitations was carried out for a specimen of innovative Fe-Si magnetic powder material. The vector experimental measurements were first performed via a single disk tester (SDT) apparatus under a controlled magnetic induction field, taking into account circular, elliptic, and scalar processes. The experimental data relative to the circular loops were utilized to identify a vector model of hysteresis based on feedforward neural networks (NNs), having as an input the magnetic induction vector B and as an output the magnetic field vector H. Then the model was validated by the simulation of the other experimental hysteresis processes. The comparison between calculated and measured loops evidenced the capability of the model in both the reconstruction of the magnetic field trajectory and the prediction of the power loss under various excitation waveforms. Finally, the computational efficiency of the model makes it s...