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Scalar Preisach Hysteresis Model Algorithm

Authors:

Veronica Manescu Paltanea,

Gheorghe Paltanea,

Iosif Vasile Nemoianu,

Radu Mircea CiuceanuAuthors Info & Claims

ECBS '19: Proceedings of the 6th Conference on the Engineering of Computer Based Systems

Article No.: 8, Pages 1 - 4

https://doi.org/10.1145/3352700.3352708

Published: 02 September 2019 Publication History

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Abstract

The Preisach model is considered a very useful tool for magnetic materials hysteresis modeling. It is very suitable for real magnetization processes, as its accuracy has been put in evidence in a large number of applications like electrical machines and transformers or magnetic recording media. In the paper it is presented a scalar Preisach model algorithm, implemented in MATLAB. The Preisach density computation is based on Biorci -- Pescetti method, using as experimental data the normal magnetization curve and the major hysteresis loop on commercial non-oriented electrical steel.

References

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I.D. Mayergoyz. 2003. Mathematical models of hysteresis and their applications. Elsevier, New York.

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F. Preisach (1935). Uber die magnetische Nachwirkung (On magnetic aftereffect). Z. Phys., 94, 277--302.

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B. Azzerboni, E. Cardelli and G. Finocchio (2004). A comparative study of Preisach scalar hysteresis models. Physica B: Condensed Matter, 343, 164--170.

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G. Biorci and D. Pescetti (1958). Analytical theory of the behavior of ferromagnetic materials. Il Nuovo Cimento, 7, 829--842.

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M. Brokate, O. Klein and P. Krejci (2006). Outward pointing properties for Preisach operators. Physica B: Condensed Matter, 372, 5--8.

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D. Pescetti (1989). Mathematical modeling of hysteresis. Il Nuovo Cimento, 11, 1191--1215.

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Cited By

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Mel HMansouri ATrabelsi H(2021)Incorporation of a Viscosity-based Model in Nonlinear Finite Element Analysis for SPM2021 18th International Multi-Conference on Systems, Signals & Devices (SSD)10.1109/SSD52085.2021.9429482(858-862)Online publication date: 22-Mar-2021
https://doi.org/10.1109/SSD52085.2021.9429482

Index Terms

Scalar Preisach Hysteresis Model Algorithm
1. Mathematics of computing
  1. Mathematical analysis

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ECBS '19: Proceedings of the 6th Conference on the Engineering of Computer Based Systems

September 2019

182 pages

ISBN:9781450376365

DOI:10.1145/3352700

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 02 September 2019

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ECBS '19

ECBS '19: 6th Conference on the Engineering of Computer Based Systems

September 2 - 3, 2019

Bucharest, Romania

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ECBS '19 Paper Acceptance Rate 25 of 49 submissions, 51%;

Overall Acceptance Rate 25 of 49 submissions, 51%

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Mel HMansouri ATrabelsi H(2021)Incorporation of a Viscosity-based Model in Nonlinear Finite Element Analysis for SPM2021 18th International Multi-Conference on Systems, Signals & Devices (SSD)10.1109/SSD52085.2021.9429482(858-862)Online publication date: 22-Mar-2021
https://doi.org/10.1109/SSD52085.2021.9429482

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A new type of neural network preisach model for hysteresis in piezoelectric actuator

Feedforward nonlinear PID control of a novel micromanipulator using Preisach hysteresis compensator

Modeling rate-dependent and thermal-drift hysteresis through preisach model and neural network optimization approach

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A new type of neural network preisach model for hysteresis in piezoelectric actuator

Feedforward nonlinear PID control of a novel micromanipulator using Preisach hysteresis compensator

Modeling rate-dependent and thermal-drift hysteresis through preisach model and neural network optimization approach

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