DocumentCode :
2016378
Title :
State-of-charge estimation based on microcontroller-implemented sigma-point Kalman filter in a modular cell balancing system for Lithium-Ion battery packs
Author :
Zhang, Fan ; Rehman, M.Muneeb Ur ; Wang, Hongjie ; Levron, Yoash ; Plett, Gregory ; Zane, Regan ; Maksimovic, Dragan
Author_Institution :
CoPEC, ECEE Department, University of Colorado Boulder, Boulder, CO 80309, USA
fYear :
2015
fDate :
12-15 July 2015
Firstpage :
1
Lastpage :
7
Abstract :
Cell balancing in large battery packs requires accurate state of charge (SOC) estimation for individual cells. This paper presents a low complexity sigma-point Kalman filter to estimate the state-of-charge (SOC) of Lithium-Ion battery cells. The proposed sigma-point Kalman filter is of 1st order, and can be easily implemented on a simple microcontroller around a dc-dc converter in a modular cell balancing system. The approach is verified experimentally on a battery pack containing twenty-one balancing converters and twenty-one 25 Ah Lithium-Ion cells under high-current (up to 100A) cycling.
Keywords :
Batteries; Estimation; Integrated circuit modeling; Kalman filters; Mathematical model; Noise; System-on-chip; BMS; Kalman filter; SOC; battery management; cell balancing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Modeling for Power Electronics (COMPEL), 2015 IEEE 16th Workshop on
Conference_Location :
Vancouver, BC, Canada
Type :
conf
DOI :
10.1109/COMPEL.2015.7236525
Filename :
7236525
Link To Document :
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