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Prognostic reliability analysis of power electronics modules

Prognostic reliability analysis of power electronics modules

Yin, Chunyan, Lu, Hua, Musallam, Mahera, Bailey, Chris and Johnson, C. Mark (2010) Prognostic reliability analysis of power electronics modules. International Journal of Performability Engineering, 6 (5):10. pp. 513-524. ISSN 0973-1318

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Abstract

This paper describes a physics-of-failure (PoF) based prognostic method for power electronics modules (PEMs). Differing from the traditional reliability prediction methods, this approach allows the reliability performance of PEMs to be assessed in real time. Four techniques have been used to develop this method, they are: (1) Compact electro-thermal model (2) Rainflow counting algorithm (3) Compact thermo-mechanical model and (4) Lifetime consumption model. As a demonstration, this method has been applied to a typical IGBT half bridge module and solder joint fatigue was assumed as the major failure mechanism. In this application, a random electric current load profile was generated in laboratory environment and used to derive the thermal loading condition for the module. Due to the randomness of the load profile, rainflow counting method was used to reduce the continuous load profile into discrete sets of thermal cycles. The damage induced in each temperature cycle was calculated via a compact thermo-mechanical model, and used in the lifetime model to calculate the PEMs lifetimes under simple cyclic loading conditions. Based on these predicted lifetimes and the linear damage accumulation rule, the total consumed life of the PEMs over the whole period of usage was predicted.

Item Type: Article
Additional Information: [1] First published in print: September 2010. [2] Published as: International Journal of Performability Engineering, (2010), Vol. 6, (5), pp. 513-524.
Uncontrolled Keywords: prognostic, reliability, power modules, physics-of-failure
Subjects: Q Science > QA Mathematics
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Pre-2014 Departments: School of Computing & Mathematical Sciences
School of Computing & Mathematical Sciences > Centre for Numerical Modelling & Process Analysis
School of Computing & Mathematical Sciences > Department of Mathematical Sciences
Related URLs:
Last Modified: 14 Oct 2016 09:11
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/4464

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