4.6 Article

Next Generation Monitoring of SiC mosfets Via Spectral Electroluminescence Sensing

期刊

IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
卷 57, 期 3, 页码 2746-2757

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIA.2021.3062773

关键词

Artificial intelligence; body diode; current sensing; electroluminescence (EL); monitoring; SiC MOSFET; temperature sensing

资金

  1. German Federal Ministry of Education and Research (BMBF) [16EMO0324, BR 6266/2-1]
  2. German Research Foundation (DFG)

向作者/读者索取更多资源

This article presents a new methodology for monitoring next generation SiC MOSFET-based converters, utilizing intelligent estimation algorithms based on artificial neural networks to separately estimate device current and junction temperature with high bandwidth. The technology can be effectively integrated into future power electronic modules, replacing external temperature and current sensors for safe and reliable long-term operation while reducing converter size and cost.
This article presents a new methodology for monitoring next generation SiC MOSFET-based converters. The methodology uses the spectral distribution of electroluminescence that is emitted by the body diodes of SiC MOSFETs and includes information on device current as well as the junction temperature. Intelligent estimation algorithms based on artificial neural networks allow processing the extracted information to separately estimate device current and junction temperature with high bandwidth. The resulting unified monitoring of device current and junction temperature galvanically isolates the sensors via optical guides from the power module. Thus, it can be effectively integrated into future power electronic modules to replace external temperature and current sensors and enable monitoring for safe and reliable long-term operation. Previous publications successfully investigated how either temperature or current information can be extracted from the intensity of the emitted light if the other variable is known. However, they did not aim to extract both variables at the same time from one measurement. This work presents how multiple optical sensors with different wavelength sensitivities and artificial-intelligence techniques can separately extract both variables. The proposed technology is evaluated using an automotive-grade SiC power module. Its utilization for monitoring future SiC-based converters allows reducing converter size and cost while increasing reliability.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据