Accuracy of IGBT junction temperature prediction: an improved sailfish algorithm to optimize support vector machine

This study improves the accuracy of junction temperature prediction, as the insulated gate bipolar transistor (IGBT) reliability is important for the safe operation of its working system due to junction temperature is limited in its actual performance and reliability. A model based on an improved sailfish optimization algorithm to optimize support vector machine (ISFO-SVM) is proposed to solve the problem that the junction temperature prediction accuracy is not high enough. The proposed algorithm is improved by adaptive nonlinear iterative factor, Le'vy flight and differential mutation strategy to optimize the support vector machine (SVM) internal parameters to predict junction temperature. The results indicate that ISFO-SVM performs better under the same evaluation indexes. The root mean squared error average value decreased by 67.189%, and the mean absolute percentage error average value decreased by 63.189%, compared with the sailfish optimization algorithm to optimize the SVM. The prediction error of ISFO-SVM is smaller and the error value is in the [-5 °C, 5 °C] range accounting for 98.270% of the total test samples. ISFO-SVM has a higher fitting degree than the actual junction temperature and the R2 has reached 99.660%. The model predicts the junction temperature of IGBT modules and provides scientific guidance for system reliability evaluation to maintain safe and stable operation effectively

Thermal analysis of Si-IGBT based power electronic modules in 50kW traction inverter application

Estimation of accurate IGBT junction temperature is crucial for reliability assessment. The well-known RC lumped approach can help predict junction temperature. However, this method suffers from inaccuracy while characterizing the thermal behaviour of several IGBT modules mounted to the liquid-cooled heatsink. Specifically, the thermal challenge originates from the thermal cross-coupling and module-to-module heat spreading and the converter cooling condition. This article demonstrates a methodology to study the impact of heat spreading, thermal interface material, and massive size liquid cold-plate on the overall thermal behaviour. A case study of 50 kW traction inverter is chosen to demonstrate the benefit of early assessment of electro-thermal simulation before making costly prototype design. Power loss is initially estimated using an analytical loss model and later the estimated power loss is used in FEA (Finite Element Analysis) thermal model. This paper also compares the performance of single-phase and two-phase liquid cooling and various thermal interface materials (TIM) to determine which type of cooling system and TIM is most suitable for real applications. Simulation results suggest that combination of two-phase liquid cooling and TIM can improve the thermal performance and reduce junction temperature by 4.5%, 4.2%, 4.6% for the traction power load 30 kW, 40 kW, and 50 kW, respectively. The proposed methodology can be used as useful reference guidance for thermal design and modelling of IGBT based power converter applications