4.4 Article

A Novel Dynamic Hysteresis Model for Grain-Oriented Electrical Steels Based on Magnetic Domain Theory

Journal

IEEE TRANSACTIONS ON MAGNETICS
Volume 58, Issue 1, Pages -

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TMAG.2021.3128765

Keywords

Magnetic hysteresis; Magnetic domains; Mathematical models; Perpendicular magnetic anisotropy; Magnetization; Magnetic flux; Steel; Dynamic modeling; energy loss; ferromagnetic materials; grain-oriented electrical steels (GOES); magnetic hysteresis

Ask authors/readers for more resources

A novel approach is developed to model the hysteresis phenomenon of grain-oriented electrical steels. The model is able to accurately replicate experimentally obtained dynamic hysteresis loops and evaluate the energy loss in the steels. There is a close agreement between the predicted energy loss and measured results.
A novel approach is adopted to model the hysteresis phenomenon of grain-oriented electrical steels (GOESs), by incorporating a variation of the domain patterns associated with ferromagnetic materials during magnetization and demagnetization. The ensuing model treats the anisotropic and isotropic components separately, together with the coupling effect of the excitation field. Its ability to replicate experimentally obtained dynamic hysteresis loops (DHLs) for Epstein size laminations of GO 3% SiFe electrical steels, for different magnetizing frequencies and peak flux densities, and facilitate the straightforward evaluation of the energy loss in GOESs is demonstrated for the case of controlled sinusoidal magnetic induction. Close agreement is found to exist between the predicted energy loss and corresponding bulk measurements, with the maximum difference being less than 2%.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.4
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available