Prognostics Health Management and Physics based failure Models for Electrolytic Capacitors

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.

Data and Resources

Additional Info

Field Value
Maintainer Miryam Strautkalns
Last Updated March 31, 2025, 23:01 (UTC)
Created March 31, 2025, 23:01 (UTC)
accessLevel public
accrualPeriodicity irregular
bureauCode {026:00}
catalog_@context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
catalog_@id https://data.nasa.gov/data.json
catalog_conformsTo 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 9fd0759b-9bcf-46a0-9f3f-84b49357a3ad
harvest_source_id 61638e72-b36c-4866-9d28-551a3062f158
harvest_source_title DNG Legacy Data
identifier DASHLINK_699
issued 2013-04-12
landingPage https://c3.nasa.gov/dashlink/resources/699/
modified 2020-01-29
programCode {026:029}
publisher Dashlink
resource-type Dataset
source_datajson_identifier true
source_hash 7558235a4760bf7c60e29ec27f19ab6ed2d6fcfa5cfd66fe07480c42d509a95d
source_schema_version 1.1