An Improved Engineering Model of Vector Magnetic Properties of Grain-Oriented Electrical Steels

Abstract

This paper presents an improved magnetic reluctivity model for vector magnetic properties of anisotropic electrical steel sheet based on Chua-type model using Fourier series expansion of measured B and H waveforms in the viewpoint of engineering application. In the modeling, B-spline surface interpolation is adopted to obtain smooth approximation of measured data. The accuracy of the proposed magnetic reluctivity model is verified by comparing its modeling results with experimentally measured B-and H-waveforms with 30PG110 grain-oriented silicon steel sheet. The nonlinear finite element (FE) formulation is also derived to incorporate the proposed reluctivity model, and applied to magnetic field analysis of a single phase transformer core model. By comparing the numerical results with experimental ones, the effectiveness of the reluctivity model and FE formulation is investigated.Index Terms-Finite element analysis, Fourier series expansion, grain-oriented silicon steel sheet, magnetic reluctivity model.

Implementation of Vector Hysteresis Model Utilizing Enhanced Neural Network Based on Collaborative Algorithm

“…Conversely, the E&S model is put forward according to the extensive amount of experimental data. Nevertheless, its reluctivity expression is significantly hard extending to the higher harmonic components for the enhancement of accuracy [10]- [12]. Some research works have introduced neural networks (NN) in hysteresis modeling, meanwhile, being constrained to the alternating magnetic field condition [13]- [20].…”