J. V. Leite, S. L.Avila, and others, “Real Coded Genetic Algorithm for Jiles-Atherton Model Parameters Identification,” IEEE Transaction on Magnetics, Vol. 34, 2004, pp 888-891.

has been cited by the following article:

• TITLE: Non Linear Magnetic Hysteresis Modelling by Finite Volume Method for Jiles-Atherton Model Optimizing by a Genetic Algorithm

  AUTHORS: Seddik Azzaoui, Kamel Srairi, Mohamed El Hachemi Benbouzid

  KEYWORDS: Magnetic Hysteresis, Jiles-Atherton Model, Genetic Algorithm Optimization, Parameters Identification, Finite Volume Method (FVM)

  JOURNAL NAME: Journal of Electromagnetic Analysis and Applications, Vol.3 No.6, June 23, 2011

  ABSTRACT: This paper describes a generalization methodology for nonlinear magnetic field calculation applied on two-dimensional (2-D) finite Volume geometry by incorporating a Jiles-Atherton scalar hysteresis model. The scheme is based upon the definition of modified governing equation derived from Maxwell’s equations considered the magnetization M. This paper shows how to extract optimal parameters for the Jiles-Atherton model of hysteresis by a real coded genetic algorithm approach. The parameters identification is performed by minimizing the mean squared error between experimental and simulated magnetic field curves. The calculated results are validated by experiences performed in an SST’s frame.