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
         
        
        
        
        
        
            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;
         
        
        
        
            Conference_Titel : 
Control and Modeling for Power Electronics (COMPEL), 2015 IEEE 16th Workshop on
         
        
            Conference_Location : 
Vancouver, BC, Canada
         
        
        
            DOI : 
10.1109/COMPEL.2015.7236525