Comparative Study of the Parameter Acquisition Methods for the Cauer Thermal Network Model of an IGBT Module

Abstract

Under the operating conditions of high power and high switching frequency, an insulated gate bipolar transistor (IGBT) chip can produce relatively large power loss, causing the junction temperature to rise rapidly; consequently, the reliability of the IGBT module can be seriously affected. Therefore, it is necessary to accurately predict the junction temperature of the IGBT chip. The resistance capacitance (RC) thermal network model is a commonly used method for IGBT junction temperature prediction. In this paper, the model parameters are obtained by two methods to establish the Cauer thermal network models of the IGBT module. The first method is to experimentally obtain the transient thermal impedance curve of the IGBT module and the structure function and then extract the individual thermal parameters of the Cauer thermal network model; the second method is to obtain the thermal parameters of the thermal network model directly by using theoretical formulas that consider the influence of the heat spreading angle. The predicted junction temperatures of the Cauer thermal network models established by the two methods are compared with the junction temperatures obtained from infrared (IR) measurements during the power cycling test, the junction temperatures measured by the temperature-sensitive electrical parameter (TSEP) method, and the junction temperatures calculated by finite element (FE) analysis. Additionally, the Cauer thermal network models established by the two methods are compared and verified. The results indicate that the Cauer thermal network model established based on theoretical formulas can accurately predict the maximum junction temperature of the IGBT chip, and the calculated temperature for each layer, from the IGBT chip layer to the ceramic layer, also accords well with the FE results. The Cauer thermal network model established based on the experimental test and the structure function can accurately predict the average junction temperature of the IGBT chip.