Li-ion battery parameter estimation for state of charge

Battery state of charge (SOC) is a critical parameter for the control of propulsion systems in plug-in hybrid electric vehicles (PHEV) and electric vehicles (EV). As SOC is not measureable during vehicle operation, an onboard adaptive algorithm is developed in this paper. The algorithm estimates six electrical parameters for Li-ion batteries and provides a reliable SOC based on one of the estimated battery parameters, i.e. open circuit voltage (OCV). Simulation and vehicle validation results show good robustness and adaptation of the algorithm with high computational efficiency and low implementation cost.

[1]  Gregory L. Plett,et al.  Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs: Part 3. State and parameter estimation , 2004 .

[2]  Gregory L. Plett,et al.  Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs Part 1. Background , 2004 .

[3]  Mark W. Verbrugge,et al.  Adaptive Energy Management of Electric and Hybrid Electric Vehicles , 2005 .

[4]  Ahmad Pesaran,et al.  Temperature-Dependent Battery Models for High-Power Lithium-Ion Batteries , 2001 .

[5]  G. Bierman.  Factorization methods for discrete sequential estimation , 1977 .

[6]  P. Kumar,et al.  Theory and practice of recursive identification , 1985, IEEE Transactions on Automatic Control.

[7]  Rolf Findeisen,et al.  State estimation of a reduced electrochemical model of a lithium-ion battery , 2010, Proceedings of the 2010 American Control Conference.

[8]  Xiaodong Zhang,et al.  Modeling and estimation of Nickel Metal Hydride battery hysteresis for SOC estimation , 2008, 2008 International Conference on Prognostics and Health Management.

[9]  B.H. Cho,et al.  The State and Parameter Estimation of an Li-Ion Battery Using a New OCV-SOC Concept , 2007, 2007 IEEE Power Electronics Specialists Conference.

[10]  Gregory L. Plett,et al.  Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs: Part 2. Modeling and identification , 2004 .

[11]  Jie Xu,et al.  EKF-Ah Based State of Charge Online Estimation for Lithium-ion Power Battery , 2009, 2009 International Conference on Computational Intelligence and Security.

[12]  Jasim Ahmed,et al.  Algorithms for Advanced Battery-Management Systems , 2010, IEEE Control Systems.

[13]  M. Verbrugge,et al.  Adaptive state of charge algorithm for nickel metal hydride batteries including hysteresis phenomena , 2004 .

[14]  Zechang Sun,et al.  Online SOC Estimation of High-power Lithium-ion Batteries Used on HEVs , 2006, 2006 IEEE International Conference on Vehicular Electronics and Safety.

[15]  Danny Sutanto,et al.  A New Battery Model for use with Battery Energy Storage Systems and Electric Vehicles Power Systems , 2000 .