A Data-Driven Modified Steinmetz Equation is Used to Predict Loss in Temperature-Sensitive Cores

In this paper, the Steinmetz equation is improved by a data-driven method, and temperature is included as an important variable to improve the accuracy of core loss prediction. This modification is verified by experimental fitting, which shows that the equation has higher accuracy and effectiveness under different temperature conditions. It is emphasized that in addition to the excitation frequency and the maximum magnetic flux density, the temperature characteristics of the material should be considered when predicting the iron loss, which has important theoretical and practical significance for the optimization of power converter and the development of efficient power conversion technology. However, the method requires a large amount of experimental data to accurately fit the model parameters, which limits its practicality. Future research should consider more influencing factors and application scenarios to further improve the applicability and prediction accuracy of the model.