Modeling the Temperature Dependence of Hysteresis Based on Jiles–Atherton Theory

Raghunathan, Arun; Melikhov, Yevgen; Snyder, John Evan; Jiles, David

doi:10.1109/tmag.2009.2022744

Cited by 82 publications

(50 citation statements)

References 10 publications

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“…12,13 According to the classical Jiles-Atherton model, the magnetization is split into irreversible and reversible components and energetic considerations will lead to the following differential equation:…”

Section: Ferromagnetic Phasementioning

confidence: 99%

“…Finally, the procedure to identify the parameters of the Jiles-Atherton model (M S , k, a, a, c) and the corresponding parameters describing their temperature dependence was established earlier 12,13 and is applicable for the measurements made at temperatures below the first order phase transition temperature, i.e., T < T 1stORDER .…”

Section: F General Identification Proceduresmentioning

confidence: 99%

“…An extended Jiles-Atherton model was proposed to successfully describe such behavior. 5,6 A more complex example is Griffiths phase in the material, i.e., in the state where coexistence of ferromagnetic and paramagnetic phases occur. Above some specific temperature, the material is in fully paramagnetic state.…”

mentioning

confidence: 99%

“…12,13 More specifically, we will refer mainly to the magnetocaloric material Gd 5 proposed approach can easily be applicable to other special systems such as systems with the Griffiths phase or other simpler systems.…”

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confidence: 99%

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Phenomenological modelling of first order phase transitions in magnetic systems

Melikhov

Hadimani

Raghunathan

2014

Journal of Applied Physics

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First order phase transitions may occur in several magnetic systems, with two structural phases having different magnetic properties each and a structural transition between them. Here, a novel physics based phenomenological model of such systems is proposed, in which magnetization is represented by the volumetric amounts of ferromagnetism (described by extended Jiles-Atherton theory) and paramagnetism (described by the Curie-Weiss law) in respective phases. An identification procedure to extract material parameters from experimental data is proposed. The proposed phenomenological approach was successfully applied to magnetocaloric Gd5(Six Ge 1−x)4 system and also has the potential to describe the behavior of Griffiths phase magnetic systems. KeywordsCurie point, Magnetic fields, Paramagnetism, Ferromagnetic materials, Magnetic materials Disciplines Electromagnetics and Photonics | Engineering Physics CommentsThe following article appeared in Journal of Applied Physics 115 (2014) First order phase transitions may occur in several magnetic systems, with two structural phases having different magnetic properties each and a structural transition between them. Here, a novel physics based phenomenological model of such systems is proposed, in which magnetization is represented by the volumetric amounts of ferromagnetism (described by extended Jiles-Atherton theory) and paramagnetism (described by the Curie-Weiss law) in respective phases. An identification procedure to extract material parameters from experimental data is proposed. The proposed phenomenological approach was successfully applied to magnetocaloric Gd 5 (Si x Ge 1Àx ) 4 system and also has the potential to describe the behavior of Griffiths phase magnetic systems. V C 2014 AIP Publishing LLC.[http://dx

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Section: Ferromagnetic Phasementioning

confidence: 99%

Section: F General Identification Proceduresmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Phenomenological modelling of first order phase transitions in magnetic systems

Melikhov

Hadimani

Raghunathan

2014

Journal of Applied Physics

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“…The iron loss can be influenced by the temperature significantly, such as [23] and [24] on ferrite cores, [25] on NiFe laminations, [26] on oriented silicon laminations, and [27]- [30] on non-oriented silicon laminations. The modeling of temperature influence on iron loss is discussed in [29] and [30].…”

Section: Introductionmentioning

confidence: 99%

A New Iron Loss Model for Temperature Dependencies of Hysteresis and Eddy Current Losses in Electrical Machines

et al. 2018

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Abstract-In this paper, the different temperature dependencies of hysteresis and eddy current losses of non-oriented Si-steel laminations are investigated. The measured iron loss results show that both the hysteresis and eddy current losses vary linearly with temperature between 40°C to 100°C, a typical temperature range of electrical machines. Varying rates of hysteresis and eddy current losses with the temperature are different and fluctuate with flux density and frequency. Based on this, an improved iron loss model which can consider temperature dependencies of hysteresis and eddy current losses separately is developed. Based on the improved iron loss model, the temperature influence on the iron loss can be fully considered by measuring iron losses at only two different temperatures. The investigation is experimentally validated by both the tests based on a ring specimen and an electrical machine.Index Terms-iron loss, eddy current loss, hysteresis loss, temperature dependency, electrical machines . In [29], only the temperature dependency of the eddy current loss is considered while the hysteresis loss is assumed to be not influenced by the temperature. In [30], the temperature influence on the total iron loss is simply modeled by introducing an equivalent temperature dependent coefficient which is a mix of temperature influences on both the hysteresis and eddy current losses. However in [27] and [28], it has shown experimentally that the hysteresis and eddy current losses have different temperature dependencies.The aim of this paper is to develop an iron loss model which can consider the temperature dependencies of the hysteresis and the eddy current losses separately. The iron losses at different flux density, frequency and temperature in non-oriented Si-steel laminations are measured firstly by the ring specimen test as will be described in Section II. In Section III, the accuracy of existing iron loss model having variable

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A Simulation Model for Narrow Band Gap Ferroelectric Materials

Ducharne

Juuti

Bai

2020

Advcd Theory and Sims

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Various ferroelectric simulation models have been developed in recent decades in order to study the mechanisms and predict the behaviors of ferroelectrics by simulating their hysteresis loops. Conventional ferroelectrics have wide optical band gaps (>2.7 eV), making them difficult to respond to visible light. Although their ferroelectricity can be affected by higher‐energy radiation like ultraviolet, little attention is paid to the development of their models incorporating light‐dependent factors. However, in recent years, narrow band gap (<2.5 eV) ferroelectrics have been discovered and are increasingly researched. These special ferroelectrics effectively absorb visible light and hence exhibit strongly light‐dependent ferroelectricity, triggering potentially a broad range of applications. Therefore, there is a need to develop a model for these ferroelectrics in order to predict their behavior under visible light. Such a model is also needed to improve the understanding of the interaction mechanisms between light and domains. In this paper, a ferroelectric simulation model based on the Jiles–Atherton theory considering light dependence is developed for the first time, and its accuracy is validated by experiments. The model shows an average error of 7.5% on polarization values compared to experimental results and thus can be employed to reliably predict photo‐induced ferroelectricity.

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Modeling the Temperature Dependence of Hysteresis Based on Jiles–Atherton Theory

Cited by 82 publications

References 10 publications

Phenomenological modelling of first order phase transitions in magnetic systems

Phenomenological modelling of first order phase transitions in magnetic systems

A New Iron Loss Model for Temperature Dependencies of Hysteresis and Eddy Current Losses in Electrical Machines

A Simulation Model for Narrow Band Gap Ferroelectric Materials

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