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A prognostic assessment method for power electronics modules

A prognostic assessment method for power electronics modules

Yin, C.Y. ORCID: 0000-0003-0298-0420, Lu, H. ORCID: 0000-0002-4392-6562, Musallam, M., Bailey, C. ORCID: 0000-0002-9438-3879 and Johnson, C. M. (2008) A prognostic assessment method for power electronics modules. In: 2nd Electronics System-Integration Technology Conference, 2008. ESTC 2008. Institute of Electrical and Electronics Engineers, Inc., Piscataway, NJ, USA, pp. 1353-1358. ISBN 978-1-4244-2814-4 (Print), 978-1-4244-2813-7 (Online) (doi:https://doi.org/10.1109/ESTC.2008.4684552)

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Abstract

This paper describes a prognostic method which combines the physics of failure models with probability reasoning algorithm. The measured real time data (temperature vs. time) was used as the loading profile for the PoF simulations. The response surface equation of the accumulated plastic strain in the solder interconnect in terms of two variables (average temperature, and temperature amplitude) was constructed. This response surface equation was incorporated into the lifetime model of solder interconnect, and therefore the remaining life time of the solder component under current loading condition was predicted. The predictions from PoF models were also used to calculate the conditional probability table for a Bayesian Network, which was used to take into account of the impacts of the health observations of each product in lifetime prediction. The prognostic prediction in the end was expressed as the probability for the product to survive the expected future usage. As a demonstration, this method was applied to an IGBT power module used for aircraft applications.

Item Type: Conference Proceedings
Title of Proceedings: 2nd Electronics System-Integration Technology Conference, 2008. ESTC 2008
Additional Information: This paper forms part of the Proceedings of the 2nd Electronics System-Integration Technology Conference, 2008 (ESTC 2008), held 1-4 September 2008, in Greenwich, London, UK. The event was organised by the Computational Mechanics and Reliability Group of the University of Greenwich and the UK and RI Chapter of IEEE Components, Packaging and Manufacturing Technology (CPMT) Society with additional input from the IEEE and iMAPS Europe and programme sponsorship from the Innovative Electronics Manufacturing Research Centre (IeMRC). ©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
Uncontrolled Keywords: power electronics modules (PEMs), reliability prediction, prognostic and health management (PHM)systems, Physics-of-failure (PoF) model, Bayesian Networks (BN)
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Q Science > QA Mathematics
Pre-2014 Departments: School of Computing & Mathematical Sciences
School of Computing & Mathematical Sciences > Centre for Numerical Modelling & Process Analysis
School of Computing & Mathematical Sciences > Centre for Numerical Modelling & Process Analysis > Computational Mechanics & Reliability Group
School of Computing & Mathematical Sciences > Department of Computer Systems Technology
School of Computing & Mathematical Sciences > Department of Mathematical Sciences
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Last Modified: 20 Mar 2019 11:54
URI: http://gala.gre.ac.uk/id/eprint/1236

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