A Dynamic Hysteresis Model for Loss Estimation of GO Silicon Steel Under DC-Biased Magnetization

A new algorithm for numerical identification of the static Preisach hysteresis model is proposed for more accurate estimation of dc-biasing hysteresis curves and hysteresis loss of the grain-oriented silicon steel sheet. Based on the experimental asymmetric major hysteresis loop under dc-biased magnetization, two sets of first-order reversal curves corresponding to ascending and descending branches, respectively, are numerically generated for construction of the Everett function. According to the equivalent field separation technique, a dynamic hysteresis model is established by parameter extraction of excess loss, and then used for simulation of dc-biasing dynamic hysteretic behaviors. The consistency between the simulated results and the measured ones demonstrates the effectiveness of the proposed method. The effect of dc bias on iron loss is analyzed as well.

Automated summary

A new algorithm for numerical identification of the static Preisach hysteresis model is proposed to accurately estimate dc-biasing hysteresis curves and hysteresis loss of grain-oriented silicon steel sheets. The algorithm constructs a dynamic hysteresis model for simulation of dc-biased dynamic hysteretic behaviors, showing effectiveness through consistency between simulated and measured results. The impact of dc bias on iron loss is also analyzed.