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Prognostic Techniques for Capacitor Degradation and Health Monitoring

Metadata Updated: December 6, 2023

This paper discusses our initial efforts in constructing physics of failure models for electrolytic capacitors subjected to electrical stressors in DC-DC power converters. Electrolytic capacitors and MOSFET’s are known to be the primary causes for degradation and failure in DC-DC converter systems. We have employed a topological energy based modeling scheme based on the bond graph (BG) modeling language for building parametric models of multi-domain systems, such as motors and pumps. In previous work, we have conducted experimental studies to validate an empirical physics of failure model based on Arrhenius Law for equivalent series resistance (ESR) increase in electrolytic capacitors operating under nominal conditions. In this paper, our focus shifts to deriving first principle models of capacitor degradation that explain both the ESR increase and the decrease in capacitance over time when the capacitor is operated under electrical stress conditions. Experimental studies are run in parallel, and data collected from these studies are used to validate the generated models. In the future, they will also be used to compute model parameters, so that the overall goal of deriving accurate models of capacitor degradation, and using them to predict performance changes in DC-DC converters is realized.

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Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

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Dates

Metadata Created Date November 12, 2020
Metadata Updated Date December 6, 2023
Data Update Frequency irregular

Metadata Source

Harvested from NASA Data.json

Additional Metadata

Resource Type Dataset
Metadata Created Date November 12, 2020
Metadata Updated Date December 6, 2023
Publisher Dashlink
Maintainer
Identifier DASHLINK_953
Data First Published 2016-02-23
Data Last Modified 2020-01-29
Public Access Level public
Data Update Frequency irregular
Bureau Code 026:00
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Metadata Catalog ID https://data.nasa.gov/data.json
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Harvest Object Id efef1b7b-d043-4d55-a7c1-53638103fb61
Harvest Source Id 58f92550-7a01-4f00-b1b2-8dc953bd598f
Harvest Source Title NASA Data.json
Homepage URL https://c3.nasa.gov/dashlink/resources/953/
Program Code 026:029
Source Datajson Identifier True
Source Hash ccad2d85749e70a1414a13ef635e979fa3fe0b511fc88fe8525af4900a87d1fd
Source Schema Version 1.1

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