Abstract-The parameters set of the Jiles-Atherton hysteresis model is identified by using a real coded genetic algorithm. The parameters identification is performed by minimizing the mean squared error between experimental and simulated magnetic field curves. The procedure is validated by comparing experimental and simulated results.
This paper deals with the incorporation of a vector hysteresis model in 2D finite-element (FE) magnetic field calculations. A previously proposed vector extension of the well-known scalar Jiles-Atherton model is considered. The vectorised hysteresis model is shown to have the same advantages as the scalar one: a limited number of parameters (which have the same value in both models) and ease of implementation. The classical magnetic vector potential FE formulation is adopted. Particular attention is paid to the resolution of the nonlinear equations by means of the Newton-Raphson method. It is shown that the application of the latter method naturally leads to the use of the differential reluctivity tensor, i.e. the derivative of the magnetic field vector with respect to the magnetic induction vector. This second rank tensor can be straightforwardly calculated for the considered hysteresis model. By way of example, the vector Jiles-Atherton is applied to two simple 2D FE models exhibiting rotational flux. The excellent convergence of the Newton-Raphson method is demonstrated.
This work proposes a modification in the Jiles-Atherton hysteresis model in order to improve the minor loops representation. The irreversible magnetization component is slightly modified keeping unchanged the other model equations and the model simplicity. Differently to other proposed methodologies found in the literature, the previously knowledge of the magnetic field waveform is not need to assure closed minor loops. Measured and calculated hysteresis curves are used in order to validate the methodology.
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