State of charge estimation for LiMn2O4 power battery based on strong tracking sigma point Kalman filter

Journal of Power Sources

Volumn 279, Issue , 2015, Pages 439-449

  Li, Di ^a   Ouyang, Jian ^a   Li, Huiqi ^b   Wan, Jiafu ^a  

^a SOUTH CHINA UNIVERSITY OF TECHNOLOGY   (China)

^b Guangzhou Electric Vehicle Co Ltd   (China)

Author keywords

Battery management system; Equivalent circuit model; Kalman filtering algorithm; Lithium ion battery; State of charge estimation; Strong tracking sigma point

Indexed keywords

ALGORITHMS; CHARGING (BATTERIES); CIRCUIT SIMULATION; CIRCUIT THEORY; ELECTRIC BATTERIES; ELECTRONIC CIRCUIT TRACKING; EXTENDED KALMAN FILTERS; KALMAN FILTERS; LITHIUM ALLOYS; LITHIUM BATTERIES; LITHIUM-ION BATTERIES; SECONDARY BATTERIES;

ELECTRICAL VEHICLES; EQUIVALENT CIRCUIT MODEL; KALMAN FILTERING ALGORITHMS; MODEL IDENTIFICATION; SIGMA POINT; SIGMA POINT KALMAN FILTER; SIMULATED RESULTS; STATE-OF-CHARGE ESTIMATION;

BATTERY MANAGEMENT SYSTEMS;

EID: 84920651407     PISSN: 03787753     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jpowsour.2015.01.002     Document Type: Article

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