Fixed-Point Harmonic-Balanced Method for DC-Biasing Hysteresis Analysis Using the Neural Network and Consuming Function
Author(s)
Zhao, Xiaojun
Lu, Junwei
Li, Lin
Li, Huiqi
Cheng, Zhiguang
Lu, Tiebing
Griffith University Author(s)
Year published
2012
Metadata
Show full item recordAbstract
The magnetic flux includes dc component and ac component in the square laminated core (SLC) under dc-biased magnetization. Hysteresis loops are distorted by dc component of magnetic field intensity in ferromagnetic core and exhibit asymmetrical and special nonlinearities. A neural network (NN) is trained on the basis of the experimental data to model hysteresis effects in the limb-yoke of the SLC. Hysteresis effects in the mitered-joint region are modeled by the consuming function combined with the dc-biasing magnetization curve. The global fixed-point magnetic reluctivity is properly determined in harmonic-balanced ...
View more >The magnetic flux includes dc component and ac component in the square laminated core (SLC) under dc-biased magnetization. Hysteresis loops are distorted by dc component of magnetic field intensity in ferromagnetic core and exhibit asymmetrical and special nonlinearities. A neural network (NN) is trained on the basis of the experimental data to model hysteresis effects in the limb-yoke of the SLC. Hysteresis effects in the mitered-joint region are modeled by the consuming function combined with the dc-biasing magnetization curve. The global fixed-point magnetic reluctivity is properly determined in harmonic-balanced finite-element method (HBFEM) to ensure globally convergent computation. The magnetic field in the SLC under dc-biased magnetization is computed by the proposed method taking account of the dc-biasing hysteresis effects.
View less >
View more >The magnetic flux includes dc component and ac component in the square laminated core (SLC) under dc-biased magnetization. Hysteresis loops are distorted by dc component of magnetic field intensity in ferromagnetic core and exhibit asymmetrical and special nonlinearities. A neural network (NN) is trained on the basis of the experimental data to model hysteresis effects in the limb-yoke of the SLC. Hysteresis effects in the mitered-joint region are modeled by the consuming function combined with the dc-biasing magnetization curve. The global fixed-point magnetic reluctivity is properly determined in harmonic-balanced finite-element method (HBFEM) to ensure globally convergent computation. The magnetic field in the SLC under dc-biased magnetization is computed by the proposed method taking account of the dc-biasing hysteresis effects.
View less >
Journal Title
IEEE Transactions on Magnetics
Volume
48
Issue
11
Subject
Physical sciences
Engineering