This work proposes a model with dynamic parameters based on the classic Jiles-Atherton model for magnetic hysteresis. The goal of this study is to investigate whether the improved model is able to generalize the material behavior correctly when minor loops are involved. Two non-linear optimization techniques are used for parameters identification: a hybrid algorithm based on Genetic Algorithm (GA), Trust-Region-Reflective (TRR) and Levemberg-Marquardt (LM), and a novel continuous technique called Continuous Flock of Starlings Optimization (CFSO). Hysteresis loops used as reference were generated with the Preisach model, and the analysis is performed on a wide set of virtual materials and excitation waveforms.
RIGANTI FULGINEI, F., Lozito, G.M., Salvini, A. (2015). A ten-parameter model for the static hysteresis simulation of ferromagnetic materials. In 2015 AEIT International Annual Conference, AEIT 2015 (pp.1-6). Institute of Electrical and Electronics Engineers Inc. [10.1109/AEIT.2015.7415264].
A ten-parameter model for the static hysteresis simulation of ferromagnetic materials
RIGANTI FULGINEI, Francesco;LOZITO, GABRIELE MARIA;SALVINI, Alessandro
2015-01-01
Abstract
This work proposes a model with dynamic parameters based on the classic Jiles-Atherton model for magnetic hysteresis. The goal of this study is to investigate whether the improved model is able to generalize the material behavior correctly when minor loops are involved. Two non-linear optimization techniques are used for parameters identification: a hybrid algorithm based on Genetic Algorithm (GA), Trust-Region-Reflective (TRR) and Levemberg-Marquardt (LM), and a novel continuous technique called Continuous Flock of Starlings Optimization (CFSO). Hysteresis loops used as reference were generated with the Preisach model, and the analysis is performed on a wide set of virtual materials and excitation waveforms.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
