A Junction Temperature Monitoring Method for IGBT Modules Based on Turn-Off Voltage With Convolutional Neural Networks

• Published in: IEEE transactions on power electronics Vol. 38; no. 8; pp. 1 - 15
• Main Authors: Wang, Huimin, Xu, Zhiliang, Ge, Xinglai, Liao, Yongkang, Yang, Yongheng, Zhang, Yi, Yao, Bo, Chai, Yuheng
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.08.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Artificial neural networks; Convolutional neural networks; Electric potential; Feature recognition; Insulated gate bipolar transistors; insulated-gate bipolar transistor (IGBT) modules; junction temperature monitoring (JTM); Junctions; load current dependence; Logic gates; Modules; Monitoring; Neural networks; Reliability analysis; Semiconductor devices; Temperature measurement; Temperature sensors; turn-off voltage; Voltage
• ISSN: 0885-8993; 1941-0107
• DOI: 10.1109/TPEL.2023.3278675

Junction temperature monitoring (JTM) is essential for reliability evaluation and health management for insulated-gate bipolar transistor (IGBT) modules, and thus is extensively focused on in power electronics converters. However, many JTM methods for IGBT modules are criticized for providing inaccurate junction temperature information with strong load current dependence. To address this, a JTM method based on the turn-off voltage (TOV) and convolutional neural networks (CNN) is proposed in this paper. In this method, the TOV is used as the junction temperature indicator, and the characterization behavior of the TOV during turn-off transient process is thoroughly analyzed. Then, the parameter dependence of the TOV is investigated. Considering the proposed JTM method may be subject to the issue of load current dependence and show an undesirable performance, the CNN is adopted to maintain the accuracy of junction temperature prediction due to its excellent global and local feature recognition capability. With this regards, the proposed JTM method enables to provide accurate junction temperature information under different conditions. Finally, the double-pulse tests and experimental tests are carried out to validate the effectiveness of the proposed JTM method.