An adaptive unscented kalman filtering approach for online estimation of model parameters and state-of-charge of lithium-ion batteries for autonomous mobile robots

IEEE Transactions on Control Systems Technology

Volumn 23, Issue 1, 2015, Pages 357-363

  Partovibakhsh, Maral ^a   Liu, Guangjun ^a  

^a RYERSON UNIVERSITY   (Canada)

Author keywords

Adaptive extended Kalman filter (AEKF); adaptive unscented Kalman filter (AUKF); lithium ion battery; online parameter estimation; state of charge (SoC).

Indexed keywords

BATTERY MANAGEMENT SYSTEMS; CHARGING (BATTERIES); ELECTRIC BATTERIES; EXTENDED KALMAN FILTERS; IONS; KALMAN FILTERS; LITHIUM; LITHIUM ALLOYS; LITHIUM COMPOUNDS; NONLINEAR FILTERING; PARAMETER ESTIMATION; SECONDARY BATTERIES;

ADAPTIVE EXTENDED KALMAN FILTERS; ADAPTIVE UNSCENTED KALMAN FILTER (AUKF); AUTONOMOUS MOBILE ROBOT; LABORATORY ENVIRONMENT; ON-LINE PARAMETER ESTIMATIONS; STATE OF CHARGE; UNSCENTED KALMAN FILTER; UNSCENTED KALMAN FILTERING;

LITHIUM-ION BATTERIES;

EID: 84919662614     PISSN: 10636536     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCST.2014.2317781     Document Type: Article

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