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.

A Reactive Power Injection Algorithm for Improving the Microgrid Operational Reliability

“…A cross-section view of the IGBT model is shown in Figure 4a, which highlights the various layers of materials used in its packaging. These layers include bond wires, silicon chips, solder layers, copper layers, a ceramic layer, and a base plate [29]. These materials have different coefficients of thermal expansion (CTE), leading to inconsistent thermal expansion behavior.…”

Steady-State Temperature-Sensitive Electrical Parameters’ Characteristics of GaN HEMT Power Devices

“…Although the physical contact method is inexpensive and noninvasive, its slow response speed makes it difficult to track dynamic junction temperature accurately [16]. While the thermal network modeling method is noninvasive, it requires extensive calculations based on accurate and continuously updated thermal network models [17,18]. In contrast, the TSEPs method, which treats the device itself as a thermal sensor, is a promising junction temperature measurement method because of its low cost, noninvasiveness, and potential for real-time on-line monitoring [19,20].…”

Simple Design Scheme for a 300 kW Modular NPC Inverter Using Thermal RC Network Analysis

“…The transient junction temperature in the modular inverter can therefore be predicted using the Foster or Cauer network, which can be easily expressed mathematically. The thermal RC network consists of values of the resistor and capacitor and is typically extracted by fitting the transient temperature response of the RC network to the actual temperature response curve, which is determined by the same step input of the power [17,18].…”