Identification of Jiles–Atherton Model Parameters Using Particle Swarm Optimization

Romain Marion (1) , Riccardo Scorretti (1) , Nicolas Siauve (1) , Marie-Ange Raulet (1) , Laurent Krähenbühl (1)

1 AMPERE - Ampère

This paper presents the use of the multiobjective particle swarm optimization (PSO) technique for the identification of Jiles–Atherton model parameters. This approach, implemented for the first time in order to solve this kind of problem, is tested for two magnetic materials: NO 3% iFe and NiFe 20–80. The results are compared with those obtained with a direct search method and a genetic algorithm procedure. Experimental measures performed on both samples of materials allow us to complete and argue the validation for the PSO method.

Mots clés: Genetic algorithms (GAs); magnetic field measurement; magnetic hysteresis; magnetic materials; modeling; optimization methods

Domaines: Energie électrique

Romain Marion, Riccardo Scorretti, Nicolas Siauve, Marie-Ange Raulet, Laurent Krähenbühl. Identification of Jiles–Atherton Model Parameters Using Particle Swarm Optimization. IEEE Transactions on Magnetics, 2008, 44 (6), pp.894-897. ⟨10.1109/TMAG.2007.914867⟩. ⟨hal-00287808⟩