Title :
An Efficient Inverted Hysteresis Model with Modified Switch Operator and Differentiable Weight Function
Author :
Bi, Shasha ; Sutor, Alexander ; Lerch, Reinhard ; Yunshi Xiao
Author_Institution :
Dept. of Sensor Technol., Univ. of Erlangen-Nuremberg, Erlangen, Germany
Abstract :
This paper proposes a different inverted hysteresis model with modification of the classic Preisach switch operator. By using this new switch operator, the inverted model remains the wiping out and congruency properties. It also guarantees the symmetry and total positiveness of weight function in the Preisach plane. According to the change pattern of H(B) branches, a differentiable weight function is introduced in the inverted model. The weight function performs with good continuity and symmetry. This makes it possible to implement the inverted model in numerical analysis without iterative procedure. The identification work is done by means of the measured major loops. Here the Newton method algorithm is applied to optimize the mean squared error (MSE) between the measured and simulated data. By this way, the limited number of parameters can be determined. The inverted model was verified for both soft and hard magnetic materials. Besides major hysteresis loops, minor loops and first-order reversal curves (FORCs) can also be simulated. By comparison, the simulation results produced by the inverted hysteresis model show good approximation to the measurement data.
Keywords :
Newton method; magnetic hysteresis; mathematical operators; Newton method algorithm; classic Preisach switch operator; congruency; continuity; differentiable weight function; first order reversal curves; hysteresis loop; inverted hysteresis model; modified switch operator; symmetry; wiping out; Iron; Magnetic hysteresis; Materials; Numerical models; Perpendicular magnetic anisotropy; Switches; Differentiable weight function; finite element method; inverted hysteresis model; switch operator;
Journal_Title :
Magnetics, IEEE Transactions on
DOI :
10.1109/TMAG.2013.2244583