Qualitative Ferromagnetic Hysteresis Modeling

Mordjaoui, M.; Chabane, M.; Boudjema, B.; Daira, R.

doi:10.3844/jcssp.2007.399.405

Cited by 8 publications

(2 citation statements)

References 22 publications

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“…In this method, the minimum parasitic capacitance is achieved by proper choice of the core type, dimensions, the number of layers and turns as well as arranging the turns and insulation [5,[7][8][9][10]14]. In [15], an approximation for the Jill-Atherton model of hysteresis loop has been propounded by ANFIS (Adaptive-Network-based Fuzzy Inference System) software. This model is useful to estimate the effective resistance related to the core losses.…”

Section: Introductionmentioning

confidence: 99%

A Straightforward Estimation Approach for Determining Parasitic Capacitance of Inductors during High Frequency Operation

Kanzi¹,

Nafissi²,

Kanzi³

2014

Journal of international Conference on Electrical Machines and

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A straightforward method for optimal determining of a high frequency inductor's parasitic capacitance is presented. The proposed estimation method is based on measuring the inductor's impedance samples over a limited frequency range bordering on the resonance point considering k-dB deviation from the maximum impedance. An optimized solution to k could be obtained by minimizing the root mean squared error between the measured and the estimated impedance values. The model used to provide the estimations is a parallel RLC circuit valid at resonance frequency which will be transferred to the real model considering the mentioned interval of frequencies. A straightforward algorithm is suggested and programmed using MATLAB which does not require a wide knowledge of design parameters and could be implemented using a spectrum analyzer. The inputs are the measured impedance samples as a function of frequency along with the diameter of the conductors. The suggested algorithm practically provides the estimated parameters of a real inductance model at different frequencies, with or without design information. The suggested work is different from designing a high frequency inductor; it is rather concentration of determining the parameters of an available real inductor that could be easily done by a recipe provided to a technician.

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Section: Introductionmentioning

confidence: 99%

A Straightforward Estimation Approach for Determining Parasitic Capacitance of Inductors during High Frequency Operation

Kanzi¹,

Nafissi²,

Kanzi³

2014

Journal of international Conference on Electrical Machines and

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show abstract

“…But the hysteresis nonlinearity affects their working performance seriously. So modeling for hysteresis nonlinearity is needed (Han et al, 2000;Gruenbichler et al, 2008;Li et al, 2007;Mordjaoui et al, 2007). The Preisach model is a hysteresis model describing the static nonlinearity of piezoelectric actuators, which was proposed by Preisach (1935) based on magnetic effect (Ping and Musa, 1997).…”

Section: Introductionmentioning

confidence: 99%

Modeling of Piezoelectric Actuators Based on Bayesian Regularization Back Propagation Neural Network

Wang¹,

Zhu²,

Wei³

et al. 2010

American Journal of Nanotechnology

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Problem statement: Piezoelectric actuator is a kind of key driving components for micropositioning stages, micropumps, micro valves, micro gripper and so on in the fields of micro/nano technology such as integrated circuit manufacturing, precision instruments, ultra precision fabrication, biomedical manipulation. It has lots of advantages including high stiffness, fast response times, less heat generating, low power consumption and large force output. But the hysteresis nonlinearity seriously affects working performance of actuators. So a lot of models were proposed to describe the hysteresis nonlinearity. A popular model which was widely used is the Preisach model. In order to obtain accurate displacement output corresponding to arbitrary input voltage with the Preisach model, function output approximation is needed. Approach: In this study, firstly the Preisach model was introduced. Then the function modeling of Preisach model based on a Bayesian Regularization Back Propagation Neural (BRBPNN) was presented and a three layers BPNN was designed. Finally, the BRBPNN was trained in Neural Network toolbox of MATLAB6.0. The Preisach function values not at equal diversion points were calculated by the trained network and the actual displacement outputs and theoretical values corresponding to random voltages input were compared. Results: Experimental results indicate that theoretical displacements and measured displacements agree with very well, the maximum displacement error is 0.35μm and the standard deviation is 0.24 μm. Conclusion: The BRBPNN could realize function approximation in Preisach modeling accurately and could meet the precision requirement in the field of modeling and controlling of piezoelectric actuators.

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Magnetic Cores

Kazimierczuk

2013

High‐Frequency Magnetic Components

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Qualitative Ferromagnetic Hysteresis Modeling

Cited by 8 publications

References 22 publications

A Straightforward Estimation Approach for Determining Parasitic Capacitance of Inductors during High Frequency Operation

A Straightforward Estimation Approach for Determining Parasitic Capacitance of Inductors during High Frequency Operation

Modeling of Piezoelectric Actuators Based on Bayesian Regularization Back Propagation Neural Network

Magnetic Cores

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