A data-driven multi-scale extended Kalman filtering based parameter and state estimation approach of lithium-ion olymer battery in electric vehicles

Applied Energy

Volumn 113, Issue , 2014, Pages 463-476

  Xiong, Rui ^a,b   Sun, Fengchun ^a   Chen, Zheng ^b   He, Hongwen ^a  

^a BEIJING INSTITUTE OF TECHNOLOGY   (China)

^b Department of Electrical and Computer Engineering   (United States)

Author keywords

Battery capacity; Data driven; Electric vehicles; Lithium ion polymer battery; Multi scale; State of Charge

Indexed keywords

ALGORITHMS; ELECTRIC VEHICLES; ESTIMATION; EXTENDED KALMAN FILTERS; LITHIUM ALLOYS;

BATTERY CAPACITY; DATA-DRIVEN; LITHIUM-ION POLYMER BATTERIES; MULTI-SCALE; STATE OF CHARGE;

PARAMETER ESTIMATION;

ACCURACY ASSESSMENT; ALGORITHM; COMMERCIALIZATION; DATA ACQUISITION; ELECTRIC VEHICLE; ELECTROCHEMICAL METHOD; ESTIMATION METHOD; EXPERIMENTAL STUDY; KALMAN FILTER; NUMERICAL MODEL; PARAMETERIZATION; POLYMER; REAL TIME; TIMESCALE;

EID: 84882945513     PISSN: 03062619     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apenergy.2013.07.061     Document Type: Article

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