NDLI: Electrochemistry-based battery modeling for prognostics

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Electrochemistry-based battery modeling for prognostics

Content Provider	NASA Technical Reports Server (NTRS)
Author	Kulkarni, Chetan Shrikant Daigle, Matthew J.
Copyright Year	2013
Description	Batteries are used in a wide variety of applications. In recent years, they have become popular as a source of power for electric vehicles such as cars, unmanned aerial vehicles, and commericial passenger aircraft. In such application domains, it becomes crucial to both monitor battery health and performance and to predict end of discharge (EOD) and end of useful life (EOL) events. To implement such technologies, it is crucial to understand how batteries work and to capture that knowledge in the form of models that can be used by monitoring, diagnosis, and prognosis algorithms. In this work, we develop electrochemistry-based models of lithium-ion batteries that capture the significant electrochemical processes, are computationally efficient, capture the effects of aging, and are of suitable accuracy for reliable EOD prediction in a variety of usage profiles. This paper reports on the progress of such a model, with results demonstrating the model validity and accurate EOD predictions.
File Size	1042854
Page Count	13
File Format	PDF
Alternate Webpage(s)	http://archive.org/details/NASA_NTRS_Archive_20140009120
Archival Resource Key	ark:/13960/t3b045441
Language	English
Publisher Date	2013-10-14
Access Restriction	Open
Subject Keyword	Battery Uncertainty Estimation Prognosis Pilotless Aircraft Passenger Aircraft Life Durability Electric Discharges Lithium Batteries Electric Motor Vehicles Electrical Measurement Algorithms Electrochemistry Mathematical Models Electric Current Metal Ions Ntrs Nasa Technical Reports Server (ntrs) Nasa Technical Reports Server Aerodynamics Aircraft Aerospace Engineering Aerospace Aeronautic Space Science
Content Type	Text
Resource Type	Article

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