Continuous Flock-of-Starlings Optimization for a general magnetic hysteresis model

Abstract

A new general typology of optimization algorithm inspired from the classical swarm intelligence, the Continuous Flock-Of-Starlings Optimization (CFSO), is used to face the inverse problem of modeling magnetic materials. It is obtained by translating the numerical swarm/flock-based algorithms into differential equations in the time domain and employing analytical closed-forms written in the continuum. The modeling of magnetic hysteresis is very important for the development of magnetic materials and the accurate design of electrical machines. Recently several hysteresis vector models have been proposed and discussed; one of them is the Vector Hysteron Model(VHM) which is a natural extension of the Preisach theory to the vector case. In this work we present a CFSO based approach for the identification of VHM in order to reproduce rotational hysteresis loops. Experimental validations are made for both NOG (Not oriented grain) and OG (Oriented grain) steels.

Keywords

Swarm intelligence inverse problems magnetic materials optimization problem vector hysteresis

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