Abstract
The insulated gate bipolar transistor (IGBT), one of the most vulnerable component, is one of the most precious central component in the converter interior. High junction temperature will lead to device failure, which is the main reason of failure of power electronic system. Therefore, on-line high precision measurement of IGBT module junction temperature is the basis of life prediction and reliability evaluation of high-power power conversion equipment. In this paper, the principle of IGBT junction temperature extraction and the latest development of related technologies are summarized. In particular, the working principle and shortcomings of temperature sensitive electrical parameter (TSEP) method are summarized. The change of junction temperature will affect the inter-electrode capacitance in the internal structure of IGBT, which will cause the change of temperature sensitive electrical parameters. The single temperature sensitive electrical parameter method is easily affected by IGBT structure and inter-electrode capacitance. This paper presents an algorithm for high precision on-line detection of IGBT junction temperature. The parameter types are optimized by stepwise regression and the model is established accordingly. In this paper, IGBT: FF50R12RT4 is used as the experimental equipment. By comparing the junction temperature model established based on multiple linear stepwise regression algorithm with the junction temperature model based on traditional temperature sensitive electrical parameters, it is proved that the algorithm has better fitting degree and precision, and the algorithm can be used for high precision online extraction of junction temperature.
Highlights
Nowadays, energy conservation and environment protection highlight the central role of power electronics technology
In this paper, a high accuracy insulated gate bipolar transistor (IGBT) junction temperature extraction method based on stepwise regression algorithm is proposed
The optimized junction temperature extraction model for IGBT is established by stepwise regression algorithm, and applied to the actual on-line monitoring, which can effectively improve the stability and reliability of power electronic devices
Summary
Energy conservation and environment protection highlight the central role of power electronics technology. When the internal temperature distribution is uneven or part of the structure is damaged, there will be a large error in single TSEP-T model On this basis, this paper selects a number of TSEPs to fit the high-precision junction temperature in the switching process, including the turn-off delay time Tdoff, current fall time Tfi, current rising time Tri, voltage rising time Trv and turn-off loss Eoff. This paper selects a number of TSEPs to fit the high-precision junction temperature in the switching process, including the turn-off delay time Tdoff, current fall time Tfi, current rising time Tri, voltage rising time Trv and turn-off loss Eoff It will be proved in the following text that the accuracy of junction temperature extraction can be improved by the model established with multi-TSEPs. The regression algorithm based on stepwise forward is taken as an example for analysis (the backward method is opposite to the forward method, all independent variables are selected into the regression model first, and the independent variables that make the model worse are gradually removed): 1) Primary selection of TSEPs; 2) Eliminate variables; 3) Stepwise regression;4) Model establishment
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