Modified FOA Applied to Parameter Extraction of Flux-Gate Core

The accuracy of the magnetic core model is important to the analysis and design of the flux-gate sensor. The Jiles-Atherton model (J-A model) is the mostly used model to describe the hysteresis characteristics of the flux-gate core. But the parameters of J-A model are difficult to identify. In this paper, Fruit Fly Optimization Algorithm (FOA) is proposed to identify the parameters of the J-A model. In order to enhance the performance of the identification, a Modified Fruit Fly Optimization Algorithm (MFOA) is applied to extract the parameters of the flux-gate core. The effectiveness of MFOA is verified through five typical test functions. The influence of variation factor h on the performance of MFOA is discussed. The impact of variation factor h on parameters extraction of hysteresis loop is studied. It is shown that MFOA with appropriate selection of variation factor h will get better performance in the accuracy, stability, and simulation time compared to those of PSO and FOA.