IGBT aging failure prediction method based on Bo-BiLSTM network
WAN Qingzhu1, YU Jiasong1, TONG Qingbin2, MIN Xianjuan1
1. School of Electric and Control Engineering, North China University of Technology, Beijing 100144; 2. School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044
Abstract Aiming at the low accuracy of aging failure prediction for insulated gate bipolar transistor (IGBT) after thermal stress impact, a bi-directional long short term memory (BiLSTM) network based on Bayesian optimization (Bo) is proposed to predict the aging failure of IGBTs. Firstly, the aging failure principle of IGBT module is analyzed, the failure characteristic database is established based on NASA aging experiment data set, and finally the Bo-BiLSTM network is constructed to predict the failure characteristic parameters by using Matlab software. Commonly used regression prediction performance evaluation indexes are selected to compare and analyze the prediction results of long short term memory (LSTM) network model, BiLSTM network model and Bo-BiLSTM network model. The results show that the model fitting accuracy of Bo-BiLSTM network is higher, so the IGBT aging failure prediction method based on Bo-BiLSTM network has better prediction effect and can be applied to IGBT failure prediction.
2024, Vol. 25 
