Prognostics Health Management and Physics based failure Models for Electrolytic Capacitors

Metadata Updated: November 12, 2020

This paper proposes first principles based modeling and prognostics approach for electrolytic capacitors. Electrolytic capacitors and MOSFETs are the two major components, which cause degradations and failures in DC-DC converters. This type of capacitors are known for its low reliability and frequent breakdown on critical systems like power supplies of avionics equipment and electrical drivers of electro-mechanical actuators. Some of the more prevalent fault effects, such as a ripple voltage surge at the power supply output can cause glitches in the GPS position and velocity output, and this, in turn, if not corrected will propagate and distort the navigation solution. Prognostics provides a way to assess remaining useful life of a capacitor based on its current state of health and its anticipated future usage and operational conditions. In this paper, we study the effects of accelerated aging due to thermal stress on sets of capacitors. Our focus is on deriving rst principles degradation models for thermal stress conditions. The degradation data form the basis for developing the model based remaining life prediction algorithm. Our overall goal is to derive accurate models of capacitor degradation, and use them to predict performance changes in DC-DC converters.

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

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Harvested from NASA Data.json

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Resource Type Dataset
Metadata Created Date November 12, 2020
Metadata Updated Date November 12, 2020
Publisher Dashlink
Unique Identifier Unknown
Maintainer
Identifier DASHLINK_699
Data First Published 2013-04-12
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
Homepage URL https://c3.nasa.gov/dashlink/resources/699/
Program Code 026:029
Source Datajson Identifier True
Source Hash 0853ca5a40b894364cb4a1db116fcfe2719369f6
Source Schema Version 1.1

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