High-Frequency Transformer Loss Measurement and Modeling: A DC Loss Method

High-frequency transformer is a key component in power electronic converters, yet accurately modeling their losses remains a big challenge. This paper introduces a novel direct current (DC) loss measurement method to model losses in two-winding high-frequency transformers. By conducting multiple tests, the DC loss method can measure the equivalent resistances of a transformer at different operating points. Instead of using conventional circuit analysis models, the proposed method utilizes an artificial neural network (ANN) to predict the losses in the excitation inverter. The ANN overcomes the difficulties caused by nonlinear parasitic parameters in inverters for loss prediction, thereby significantly enhancing measurement accuracy. A testing platform based on the proposed method was constructed, and the loss models of several high-frequency transformers were measured. The measurement results were compared with those obtained using the Finite Element Method (FEM) and impedance analyzer, demonstrating the high accuracy of the proposed method.