Automatic and accurate evaluation of the parameters of the magnetic hysteresis model

This paper presents a method based on both Artificial Neural Networks (ANNs) and on a multidimensional optimisation procedure in order to significantly reduce the time taken and to improve the accuracy in evaluating parameters of the Jiles-Atherton´s model of magnetic hysteresis. The main steps of the method can be individualised as: (i) data acquisition of the experimental hysteresis loop of the magnetic material under test, (ii) evaluation of the model´s parameters by means of the ANN, and (iii) parameter accuracy improvement by means of a multidimensional optimisation procedure. In order to highlight the method´s effectiveness, the results of numerical and experimental tests are also given