电源学报2025，Vol.23Issue(1)：229-235,258,8.DOI:10.13234/j.issn.2095-2805.2025.1.229
基于PSO-BP神经网络的SiC MOSFET模块寿命预测方法研究与实现
Research and Implementation of Life Prediction Method for SiC MOSFET Module Based on PSO-BP Neural Network
毛明波 1孟昭亮 2高勇 1杨媛3
作者信息
- 1. 西安工程大学电子信息学院,西安 710699
- 2. 西安工程大学电子信息学院,西安 710699||西安理工大学国际工学院,西安 710048||中车永济电机有限公司电力电子事业部,西安 710000
- 3. 西安理工大学国际工学院,西安 710048
- 折叠
摘要
Abstract
To solve the difficulty in online life prediction of silicon carbide metal-oxide-semiconductor field-effect transistor(SiC MOSFET)under practical working conditions,a digital implementation method for SiC MOSFET module life prediction based on particle swarm optimization-back propagation(PSO-BP)neural network was proposed.First,the saturation voltage drop of SiC MOSFET was extracted by a saturation voltage drop platform as the temperature-sensitive electric parameter,and a junction temperature prediction scheme based on experimental data was established.Second,a life prediction scheme based on PSO-BP neural network was established by using a power cycling accelerated aging experimental platform to extract the aging characteristic data.Third,the junction temperature prediction scheme and life prediction scheme were transplanted to field programmable gate array to realize the digitization of SiC MOSFET life prediction.Finally,a circuit was designed to verify the proposed method.Experimental results show that the error between the digital junction temperature and real junction temperature was 4.73℃,and the percentage of error between the predicted life times and real life times was 4.1%,which proves that the proposed life prediction method is realized digitally and can accurately predict the life times of SiC MOSFET module.关键词
SiC MOSFET/粒子群优化-反向传播/寿命预测/数字化Key words
Silicon carbide metal-oxide-semiconductor field-effect transistor(SiC MOSFET)/particle swarm optim-ization-back propagation(PSO-BP)/life prediction/digitization分类
电子信息工程引用本文复制引用
毛明波,孟昭亮,高勇,杨媛..基于PSO-BP神经网络的SiC MOSFET模块寿命预测方法研究与实现[J].电源学报,2025,23(1):229-235,258,8.
