Estimation of State of Charge for Lithium-Ion Battery Based on Finite Difference Extended Kalman Filter

An accurate estimation of the state of charge (SOC) of the battery is of great significance for safe and efficient energy utilization of electric vehicles. Given the nonlinear dynamic system of the lithium-ion battery, the parameters of the second-order RC equivalent circuit model were calibrated and optimized using a nonlinear least squares algorithm in the Simulink parameter estimation toolbox. A comparison was made between this finite difference extended Kalman filter (FDEKF) and the standard extended Kalman filter in the SOC estimation. The results show that the model can essentially predict the dynamic voltage behavior of the lithium-ion battery, and the FDEKF algorithm can maintain good accuracy in the estimation process and has strong robustness against modeling error.

[1]  C. Moo,et al.  Enhanced coulomb counting method for estimating state-of-charge and state-of-health of lithium-ion batteries , 2009 .

[2]  Magdi S. Mahmoud,et al.  State and Parameter Estimation , 1984 .

[3]  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 .

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

[5]  Valerie H. Johnson,et al.  Battery performance models in ADVISOR , 2002 .

[6]  Suleiman Abu-Sharkh,et al.  Rapid test and non-linear model characterisation of solid-state lithium-ion batteries , 2004 .

[7]  Xiaosong Hu,et al.  A comparative study of equivalent circuit models for Li-ion batteries , 2012 .

[8]  Uzay Kaymak,et al.  Modeling and Identification , 2002 .

[9]  Hongwen He,et al.  Online model-based estimation of state-of-charge and open-circuit voltage of lithium-ion batteries in electric vehicles , 2012 .

[10]  Yi-Hsien Chiang,et al.  Online estimation of internal resistance and open-circuit voltage of lithium-ion batteries in electr , 2011 .

[11]  Tor Steinar Schei,et al.  A finite-difference method for linearization in nonlinear estimation algorithms , 1997, Autom..

[12]  T. Schei.  A finite-difference method for linearization in nonlinear estimation algorithms , 1998 .

[13]  Jianqiu Li,et al.  A review on the key issues for lithium-ion battery management in electric vehicles , 2013 .

[14]  G. Plett.  LiPB Dynamic Cell Models for Kalman-Filter SOC Estimation , 2002 .

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

[16]  M. Meyer,et al.  Study of the local SOC distribution in a lithium-ion battery by physical and electrochemical modeling and simulation , 2013 .

[17]  Ming Jiang,et al.  Research on PNGV model parameter identification of LiFePO4 Li-ion battery based on FMRLS , 2011, 2011 6th IEEE Conference on Industrial Electronics and Applications.

[18]  Hongwen He,et al.  State-of-Charge Estimation of the Lithium-Ion Battery Using an Adaptive Extended Kalman Filter Based on an Improved Thevenin Model , 2011, IEEE Transactions on Vehicular Technology.