A naive bayes model for robust remaining useful life prediction of lithium-ion battery

Applied Energy

Volumn 118, Issue , 2014, Pages 114-123

  Ng, Selina S Y ^a   Xing, Yinjiao ^a   Tsui, Kwok L ^a  

^a CITY UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Lithium ion battery; Naive Bayes; Prediction; Prognostic; Remaining useful life; State of health

Indexed keywords

BARIUM COMPOUNDS; BATTERY MANAGEMENT SYSTEMS; BAYESIAN NETWORKS; CLASSIFIERS; FORECASTING; IONS; LITHIUM COMPOUNDS; SUPPORT VECTOR MACHINES; TEMPERATURE;

DIFFERENT OPERATING CONDITIONS; ENVIRONMENTAL CONDITIONS; NAIVE BAYES; PREDICTION PERFORMANCE; PROGNOSTIC; REMAINING USEFUL LIFE PREDICTIONS; REMAINING USEFUL LIVES; STATE OF HEALTH;

LITHIUM-ION BATTERIES;

BIODEGRADATION; DISCHARGE; ION; LITHIUM; NUMERICAL MODEL; PERFORMANCE ASSESSMENT; PREDICTION; TEMPERATURE EFFECT;

EID: 84891898576     PISSN: 03062619     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apenergy.2013.12.020     Document Type: Article

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