An Improved Model for Anomalous Loss Utilizing Loss Separation and Comparison With ANN Model in Electrical Steel Sheet

Abstract

This article investigates the behavior of anomalous magnetic field in electrical steel sheet (ESS). For this, anomalous magnetic field is extracted from measured magnetic field by excluding static hysteresis and eddy current fields. To overcome the shortcomings of the Bertotti’s and artificial neural network (ANN) models for anomalous magnetic field and loss, an improved model is proposed by introducing a new parameter, time shifting, to modify the phase of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$B$ </tex-math></inline-formula> -waveform. Through comparisons of Bertotti’s model, ANN model, and experimental measurements over non-oriented, highly grain-oriented, and domain-refined highly grain-oriented ESSs, the proposed model is validated.