Research On Junction Temperature Measurement Method Of Power Module IGBT

With the continuous improvement of the manufacturing process of power electronic devices and the gradual improvement of semiconductor converter technique,insulated gate bipolar transistor(IGBT),as the core components of power converter devices,has been widely used in energy-saving fields such as electric vehicles and smart grids and new energy fields such as wind energy and solar power generation.Therefore,ensure reliable and safe operation of the IGBT power module is of great significance to solve the energy crisis and promote the sustainable and stable development of energy saving and new energy industry.The junction temperature of IGBT is the electrical parameter which is closely related to the reliability of IGBT power module,it is necessary to realize the accurate measurement and prediction of the junction temperature of the IGBT module in the aging process and control the junction temperature.It is of great significance to master the aging degree of the IGBT module,prolong the service life of the IGBT module and improve the reliability of the IGBT module.The main research works are as follows:Firstly,the basic structure and working characteristics of IGBT are briefly introduced.From the perspective of the package structure,the heat transfer mechanism of the IGBT is analyzed.Based on the above research contents,the failure modes associated with the chip level and the failure modes associated with the package are analyzed.It is revealed that the junction temperature and the frequent fluctuation of junction temperature are the key factor that affecting the reliability of the IGBT module,which laid the foundation for further development of junction temperature calculation.Based on the comparison and analysis of various junction temperature measurement methods,considering the influence of the aging of the module and the accuracy of the junction temperature measurement,the method of measuring the junction temperature with saturated voltage drop as the temperature sensitive parameter is selected.Secondly,the relationship between external parameter saturation voltage drop and internal parameter junction temperature is established through theoretical analysis.However,considering the aging of the IGBT power module has an impact on the method of measuring junction temperature by saturation voltage drop as temperature sensitive parameter.Therefore,in order to explore the changes in the parameters and their relationship in the aging process,power cycle aging test and single pulse thermostat test was designed to obtain power cycle aging times,saturation voltage drop,collector current and junction temperature in the power cycle aging process.Thirdly,the three-dimensional surface relationship of saturation voltage drop,collector current and junction temperature in the aging process has not changed significantly,and there is still a good correlation between the three.Therefore,keeping the other parameters unchanged,one by one analysis the relationship between saturation voltage drop and power cycle aging times,collector current and junction temperature in the aging process.Considering the influence of each parameter on the saturation voltage drop,the junction temperature polynomial prediction model is obtained.Moreover,the junction temperature polynomial prediction model can predict the junction temperature accuracy.Finally,in order to solve the problem that the accuracy of the junction temperature polynomial prediction model is affected under the condition of high temperature and current,an improved firefly algorithm optimization support vector machine model(IFA-SVM)is proposed and applied to the IGBT junction temperature prediction.The effect of improved firefly algorithm optimization support vector machine model(IFA-SVM),firefly algorithm optimization support vector machine model(FA-SVM)and junction temperature polynomial prediction model on the prediction results of junction temperature are compared,and it is found that the prediction accuracy of the improved firefly algorithm optimization support vector machine model(IFA-SVM)is much higher than that of the junction temperature polynomial prediction model,and superior to the firefly optimization support vector machine model(FA-SVM).Therefore,the improved firefly algorithm optimization support vector machine model(IFA-SVM)not only can better predict the junction temperature of IGBT,but also has important significance for improving the reliability of IGBT.