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Prognostics Approach for Power MOSFET Under Thermal-StressThe prognostic technique for a power MOSFET presented in this paper is based on accelerated aging of MOSFET IRF520Npbf in a TO-220 package. The methodology utilizes thermal and power cycling to accelerate the life of the devices. The major failure mechanism for the stress conditions is dieattachment degradation, typical for discrete devices with leadfree solder die attachment. It has been determined that dieattach degradation results in an increase in ON-state resistance due to its dependence on junction temperature. Increasing resistance, thus, can be used as a precursor of failure for the die-attach failure mechanism under thermal stress. A feature based on normalized ON-resistance is computed from in-situ measurements of the electro-thermal response. An Extended Kalman filter is used as a model-based prognostics techniques based on the Bayesian tracking framework. The proposed prognostics technique reports on preliminary work that serves as a case study on the prediction of remaining life of power MOSFETs and builds upon the work presented in [1]. The algorithm considered in this study had been used as prognostics algorithm in different applications and is regarded as suitable candidate for component level prognostics. This work attempts to further the validation of such algorithm by presenting it with real degradation data including measurements from real sensors, which include all the complications (noise, bias, etc.) that are regularly not captured on simulated degradation data. The algorithm is developed and tested on the accelerated aging test timescale. In real world operation, the timescale of the degradation process and therefore the RUL predictions will be considerable larger. It is hypothesized that even though the timescale will be larger, it remains constant through the degradation process and the algorithm and model would still apply under the slower degradation process. By using accelerated aging data with actual device measurements and real sensors (no simulated behavior), we are attempting to assess how such algorithm behaves under realistic conditions.
Document ID
20140010629
Acquisition Source
Ames Research Center
Document Type
Conference Paper
Authors
Galvan, Jose Ramon Celaya (Stinger Ghaffarian Technologies, Inc. (SGT, Inc.) Moffett Field, CA, United States)
Saxena, Abhinav (Stinger Ghaffarian Technologies, Inc. (SGT, Inc.) Moffett Field, CA, United States)
Kulkarni, Chetan S. (Vanderbilt Univ. Nashville, TN, United States)
Saha, Sankalita (MCT, Inc. Moffett Field, CA, United States)
Goebel, Kai (NASA Ames Research Center Moffett Field, CA, United States)
Date Acquired
August 13, 2014
Publication Date
January 23, 2012
Subject Category
Electronics And Electrical Engineering
Report/Patent Number
ARC-E-DAA-TN4409
Meeting Information
Meeting: The Annual Reliability and Maintainability Symposium
Location: Reno, NV
Country: United States
Start Date: January 23, 2012
End Date: January 26, 2012
Sponsors: Institute of Electrical and Electronics Engineers
Funding Number(s)
CONTRACT_GRANT: NNA08CG83C
Distribution Limits
Public
Copyright
Public Use Permitted.
Keywords
Power MOSFET PHM
Prognostics
Electronics Prognostics

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