Inverse Rheological Hysteresis Model and its Efficient Parameter Identification Method

An inverse rheological hysteresis model is proposed in this article, and to avoid the problem of requiring too much experimental data for identifying this model, an efficient and practical parameter determination method is thus developed based on combining the genetic algorithm and the numerical method of producing the first-order reversal curves (FORCs). This inverse rheological hysteresis model and its related parameter identification method are subsequently applied to simulate the different kinds of hysteresis loops of soft magnetic materials, which are symmetrical loops and major loops embedded with the asymmetrical dc-biased minor loops. By comparing these predicted loops with those measured, the accuracy and practicability of the proposed hysteresis model and its identification method are verified, showing appealing features in the fields that need to simulate the hysteresis properties of soft magnetic materials accurately and fast under different kinds of excitations including the complex non-sinusoidal excitations.