Three-Dimensional Thermal Network Modeling and Temperature Rise Prediction of Nanocrystalline High-Frequency Transformer

The internal hotspot temperature rise prediction in nanocrystalline high-frequency transformers (nanoHFTs) is essential to ensure reliable operation. This paper presents a three-dimensional thermal network (3DTN) model for epoxy resin encapsulated nanoHFTs, which aims to precisely predict the temperature distribution inside the transformer in combination with the finite element method (FEM). A magnetothermal bidirectional coupling 3DTN model is established by analyzing the thermal conduction between the core, windings, and epoxy resin, while also considering the convection and radiation heat transfer mechanisms on the surface of the epoxy resin. The model considers the impact of loss distribution in the core and windings on the temperature field and adopts a simplified 1/2 thermal network model to reduce computational complexity. Furthermore, the results of FEM are compared with experimental results to verify the accuracy of the 3DTN model in predicting the temperature rise of nanoHFT. The results show that the 3DTN model reduces errors by an average of 5.25% over the traditional two-dimensional thermal network (2DTN) model, particularly for temperature distributions in the windings and core. This paper provides a temperature rise prediction method for the thermal design and offers a theoretical basis and engineering guidance for the optimization of their thermal management systems.