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Author Gasper, Paul, author.

Title Predictive battery lifetime modeling at the National Renewable Energy Laboratory / Paul Gasper, Kandler Smith.

Publication Info. [Golden, CO] : National Renewable Energy Laboratory, 2021.

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Description 1 online resource (38 pages) : illustrations (chiefly color).
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Series NREL/PR ; 5700-80158
NREL/PR ; 5700-80158.
Note "Battery Modeling Webinar Series"--Cover.
"Energy Conversion and Storage Systems Center Electrochemical Energy Storage"--Cover.
Bibliography Includes bibliographical references.
Funding U.S. Department of Energy DE-AC36-08GO28308
Note Description based on online resource, PDF version; title from cover (NREL, viewed on June 3, 2022).
Summary Overview of the development of algebraic battery lifetime modeling efforts within NREL's Electrochemical Energy Storage group within the Energy Conversion and Storage Systems Center. Traditional approaches to developing battery lifetime models are compared with a new methodology incorporating machine learning to autonomously identify parsimonious model equations.
Subject Mathematical models.
Renewable energy sources -- United States.
Énergies renouvelables -- États-Unis.
Mathematical models
Renewable energy sources
United States https://id.oclc.org/worldcat/entity/E39PBJtxgQXMWqmjMjjwXRHgrq
Indexed Term aging
battery
lifetime
machine-learning
prediction
Added Author Smith, Kandler, author.
National Renewable Energy Laboratory (U.S.), issuing body.
Standard No. 1838001 OSTI ID
0000-0001-8834-9458
0000-0001-7011-0377
Gpo Item No. 0430-P-09 (online)
Sudoc No. E 9.22:NREL/PR-5700-80158

 
    
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