| Popis: |
Accurate analysis and optimal operation of electromagnetic devices can only be predicted by a robust modeling of ferromagnetic materials. In this context, several hysteresis models have been proposed. The Jiles-Atherton model [1] is commonly used, it is among the main studied in the literature. However, it requires robust identification process of five interdependent parameters, based on experimental hysteresis loop. In a recent paper, the artificial bee colony ABC method, inspired by the collective behavior of bees [2] is applied for the identification [3]. The present work deals about comparison between the ABC method and the particle swarm optimization method PSO [4], which is based on the motion of swarms of birds and fishes. The objective of this study is to give performance of both algorithms in computing time, iteration numbers and parameter estimation. Finally, obtained hysteresis loops is compared to experiment data. |
