Data-driven prognostics for lithium-ion battery based on Gaussian process regression

Proceedings of IEEE 2012 Prognostics and System Health Management Conference, PHM-2012

Volumn , Issue , 2012, Pages

  Liu, Datong ^a   Pang, Jingyue ^a   Zhou, Jianbao ^a   Peng, Yu ^a  

^a HARBIN INSTITUTE OF TECHNOLOGY   (China)

Author keywords

Capacity Prediction; Dynamic Model; Gaussian Process Regression; Lithium ion Battery; Prognostcis and Health Management; State of Health; Uncertainty

Indexed keywords

CAPACITY PREDICTION; GAUSSIAN PROCESS REGRESSION; HEALTH MANAGEMENT; LITHIUM-ION BATTERY; STATE OF HEALTH; UNCERTAINTY;

ALGORITHMS; DYNAMIC MODELS; ELECTRIC VEHICLES; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); LITHIUM BATTERIES; MEASUREMENT ERRORS; SYSTEMS ENGINEERING; UNCERTAINTY ANALYSIS;

FORECASTING;

EID: 84866150870     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/PHM.2012.6228848     Document Type: Conference Paper

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