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Author:

Li, Yaosheng (Li, Yaosheng.) | Chen, Zhongyuan (Chen, Zhongyuan.) | Li, Jinyuan (Li, Jinyuan.) | Guo, Chunsheng (Guo, Chunsheng.)

Indexed by:

EI Scopus

Abstract:

Accelerated degradation test is one of the commonly used reliability test methods for power semiconductor devices. Its principle is to implement the working conditions of the devices that exceed normal strength based on scientific theoretical derivation and the device's thermoelectric model, thereby changing the aging environment of the devices during test to analyze the degradation of device's parameters. In accelerated degradation test, one of the commonly used methods is to change the working junction temperature of the device through the constant current test. IGBT as a high-power electronic device, its working condition is usually a large current or voltage, which will cause the device to have an high junction temperature, and this situation will lead to device damage. The research content of this paper is mainly aim at the IGBT device in the accelerated degradation test, and a more accurate junction temperature measurement method is proposed than traditional methods. © 2020 IEEE.

Keyword:

Artificial intelligence Temperature measurement Insulated gate bipolar transistors (IGBT) Semiconductor junctions

Author Community:

  • [ 1 ] [Li, Yaosheng]State Key Laboratory of Advanced Power Transmission Technology, Beijing, China
  • [ 2 ] [Chen, Zhongyuan]State Key Laboratory of Advanced Power Transmission Technology, Beijing, China
  • [ 3 ] [Li, Jinyuan]State Key Laboratory of Advanced Power Transmission Technology, Beijing, China
  • [ 4 ] [Guo, Chunsheng]Faculty of Information Technology, Beijing University of Technology, Beijing, China

Reprint Author's Address:

  • [guo, chunsheng]faculty of information technology, beijing university of technology, beijing, china

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Source :

Year: 2020

Page: 51-55

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 2

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 13

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