Lithium-ion battery state of health monitoring and remaining useful life prediction based on support vector regression-particle filter

Journal of Power Sources

Volumn 271, Issue , 2014, Pages 114-123

  Dong, Hancheng ^a,b   Jin, Xiaoning ^b   Lou, Yangbing ^b   Wang, Changhong ^a  

^a HARBIN INSTITUTE OF TECHNOLOGY   (China)

^b UNIVERSITY OF MICHIGAN   (United States)

Author keywords

Capacity degradation parameter; Lithium ion battery; Remaining useful life; RUL prediction model; State of health; Support vector regression particle filter

Indexed keywords

BATTERY MANAGEMENT SYSTEMS; FORECASTING; IONS; MONTE CARLO METHODS; PREDICTIVE ANALYTICS; PROBABILITY DISTRIBUTIONS; SUPPORT VECTOR REGRESSION;

CAPACITY DEGRADATION; PARTICLE FILTER; REMAINING USEFUL LIVES; RUL PREDICTIONS; STATE OF HEALTH;

LITHIUM-ION BATTERIES;

EID: 84906237663     PISSN: 03787753     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jpowsour.2014.07.176     Document Type: Article

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