A neural network for incorporating the thermal effect on the magnetic hysteresis of the 3F3 material using the Jiles–Atherton model

• We incorporate the thermal effect on the magnetic hysteresis of the 3F3 material.
• We use the Jiles–Atherton model.
• A neural network is used to learn the variation of Ms and Hc with the temperature.
• k≈Hc, the rest of the J–A model parameters (α, c) are calculated analytically.
• The parameter a is treated as a constant.

The present paper deals with the temperature dependent modeling approach for the generation of hysteresis loops of ferromagnetic materials. The physical model is developed to study the effect of temperature on the magnetic hysteresis loop using the Jiles–Atherton (J–A) model. The thermal effects were incorporated through temperature dependent hysteresis parameters of JA model. The temperature-dependent J–A model was validated by measurements made on the ferrite material. The results of proposed model were in good agreement with the measurements.