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.