The Parameters Identification of Magnetic Core Using Fruit Fly Optimization Algorithm

This paper is concerned about the parameters identification of the Jiles-Atherton hysteresis loop model using Fruit Fly Optimization Algorithm (FOA). An improved Fruit Fly optimization algorithm (IFOA) is proposed to overcome the drawback of FOA, such as easily falling into local optimum, low precision, and poor stability. The IFOA has been applied to identify Jiles-Atherton model parameters of conventional non-oriented electrical steel. The simulation results are compared with those of FOA and Particle Swarm Optimization (PSO), which shows the modelled M H curve obtained with IFOA is in good agreement with the measured M H curve and IFOA method has the advantages of better global searching ability, higher precision and stability.