A simple method to determine dynamic hysteresis loops of soft magnetic materials

Schmidt, Nicola; Güldner, H.

doi:10.1109/20.486537

Cited by 40 publications

(21 citation statements)

References 5 publications

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“…Prozygy [5] attacked the issue of understanding the Jiles-Atherton model parameters from a different perspective and used simple variational techniques to demonstrate the relationship between parameter variations and the main effects of the hysteresis loop, e.g., varying the parameter was responsible primarily for the loop height. More recently, Schmidt and Güldner [6] used the model as the core of an optimization approach to fit curve data and this was also used by Lederer et al [7] to propose modifications to the original model to handle the variations in parameters between minor and major loops.…”

Section: Introductionmentioning

confidence: 99%

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Definition and application of magnetic material metrics in modeling and optimization

Wilson

Ross

2001

IEEE Trans. Magn.

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Abstract-The modeling of magnetic components for use in electrical circuit simulation requires that the core material be accurately characterized. This paper investigates a method of extracting parameters to model the hysteresis behavior of magnetic core materials and optimizing them to achieve accurate results during circuit simulation. Metrics are defined to measure specific features of the behavior of both the core magnetic material and the magnetic component, such as a transformer. This paper presents a method of applying these metrics for the purposes of comparison and optimization and demonstrates the method using measured results and corresponding simulations. It compares the effectiveness of a weighted metrics function with that of a least squares goal function for the purpose of optimization. This paper suggests modifications to the original Jiles-Atherton model to improve the ability of the model to more accurately represent the behavior of magnetic materials during saturation.

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Section: Introductionmentioning

confidence: 99%

“…The first issue is how to define the performance of a model in an appropriate way. The optimization technique used in [6] used a least squares fit approach. This does consider the key features in the model that may have different relative importance depending on the application, which are not taken into account in the optimization process.…”

Section: Introductionmentioning

confidence: 99%

Definition and application of magnetic material metrics in modeling and optimization

Wilson

Ross

2001

IEEE Trans. Magn.

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“…If the prediction error {ε(t k )} N t k =max(n α ,n β )+1 is white noise, an estimate of the model parameters θ can be solved using the least squares aŝ (10) where…”

Section: B Indirect Continuous-time Model Identificationmentioning

confidence: 99%

Nonlinear Dynamic Transformer Time-Domain Identification for Power Converter Applications

O’Driscoll

Ringwood

2014

IEEE Trans. Power Electron.

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Abstract-For flyback converter applications, an accurate model of the transformer is necessary for simulation studies, as well as a basis for model-based controller design. In general, transformer modeling has either focused on the winding model, using frequency-domain methods, or on the nonlinear core model, using time-domain methods. Nonlinear modeling is confined to the time domain and certain difficulties have precluded the use of timedomain methods for winding model estimation, resulting in the lack of integrated modeling approaches. This paper focuses on identifying a complete nonlinear dynamic model of a 3-winding transformer using time-domain system identification approaches. Our study demonstrates a possible way to handle the difficulties of working in the time domain and provides a model at least as accurate as that obtained with the frequency response data. In addition to the parameters of the Jiles-Atherton model, which is used to describe the nonlinear core behavior, the air-gap length is also computed from the experimental data to enhance the core model accuracy. The obtained transformer winding model, core model, and full model are experimentally verified.

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“…The materials were plated onto 6 m thick insulation and an additional adhesive tape was used to provide mechanical strength. Loss measurements were carried out using the transformer method [16], with compensation included for the delay of the current probe and air-core leakage effects. As shown, both materials provide improved loss properties compared to 4F1 up to 5 MHz, with Alloy 1 providing the best performance.…”

Section: Electroplated Alloy Core Materialsmentioning

confidence: 99%

High current inductor design for MHz switching

Duffy¹,

Collins²,

Rhen³

et al. 2008

2008 IEEE Power Electronics Specialists Conference

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A simple method to determine dynamic hysteresis loops of soft magnetic materials

Cited by 40 publications

References 5 publications

Definition and application of magnetic material metrics in modeling and optimization

Definition and application of magnetic material metrics in modeling and optimization

Nonlinear Dynamic Transformer Time-Domain Identification for Power Converter Applications

High current inductor design for MHz switching

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