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Estimating the State-of-Charge of Lithium-Ion Batteries Using an H-Infinity Observer with Consideration of the Hysteresis Characteristic
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  • Journal title : Journal of Power Electronics
  • Volume 16, Issue 2,  2016, pp.643-653
  • Publisher : The Korean Institute of Power Electronics
  • DOI : 10.6113/JPE.2016.16.2.643
 Title & Authors
Estimating the State-of-Charge of Lithium-Ion Batteries Using an H-Infinity Observer with Consideration of the Hysteresis Characteristic
Xie, Jiale; Ma, Jiachen; Sun, Yude; Li, Zonglin;
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The conventional methods used to evaluate battery state-of-charge (SOC) cannot accommodate the chemistry nonlinearities, measurement inaccuracies and parameter perturbations involved in estimation systems. In this paper, an impedance-based equivalent circuit model has been constructed with respect to a LiFePO4 battery by approximating the electrochemical impedance spectrum (EIS) with RC circuits. The efficiencies of approximating the EIS with RC networks in different series-parallel forms are first discussed. Additionally, the typical hysteresis characteristic is modeled through an empirical approach. Subsequently, a methodology incorporating an H-infinity observer designated for open-circuit voltage (OCV) observation and a hysteresis model developed for OCV-SOC mapping is proposed. Thereafter, evaluation experiments under FUDS and UDDS test cycles are undertaken with varying temperatures and different current-sense bias. Experimental comparisons, in comparison with the EKF based method, indicate that the proposed SOC estimator is more effective and robust. Moreover, test results on a group of Li-ion batteries, from different manufacturers and of different chemistries, show that the proposed method has high generalization capability for all the three types of Li-ion batteries.
H-infinity observer;Hysteresis characteristic;Impedance-based modeling;State-of-charge;
 Cited by
M. A. Roscher and D. U. Sauer, “Dynamic electric behavior and open-circuit-voltage modeling of LiFePO4-based lithium ion secondary batteries,” Journal of Power Sources, Vol. 196, No. 1, pp. 331-336, Jan. 2011. crossref(new window)

Y. He, X. T. Liu, C. B. Zhang, and Z. H. Chen, “A new model for state-of-charge(SOC) estimation for high-power Li-ion batteries,” Applied Energy, Vol. 101, pp. 808-814, Jan. 2013. crossref(new window)

S. Piller, M. Perrin, and A. Jossen, “Methods for state-of-charge determination and their applications,” Journal of power sources, Vol. 96, No. 1, pp. 113-120, Jun. 2001. crossref(new window)

K. S. Ng, C.-S. Moo, Y.-P. Chen, and Y.-C. Hsieh, “Enhanced coulomb counting method for estimating state-of-charge and state-of-health of lithium-ion batteries,” Applied energy, Vol. 86, No. 9, pp. 1506-1511, Sep. 2009. crossref(new window)

S. Lee, J. Kim, J. Lee, and B. H. Cho, “State-of-charge and capacity estimation of lithium-ion battery using a new open-circuit voltage versus state-of-charge,” Journal of power sources, Vol. 185, No. 2, pp. 1367-1373, Dec. 2008. crossref(new window)

P. Spagnol, S. Rossi, and S. M. Savaresi, "Kalman filter SOC estimation for Li-ion batteries," in IEEE International Conference on Control Applications(CCA), pp. 587-592, Sep. 2011.

M. Charkhgard and M. Farrokhi, “State-of-charge estimation for lithium-ion batteries using neural networks and EKF,” IEEE Trans. Ind. Electron., Vol. 57, No. 12, pp. 4178-4187, Dec. 2010. crossref(new window)

W. He, N. Williard, C. Chen, and M. Pecht, “State of charge estimation for electric vehicle batteries using unscented Kalman filtering,” Microelectronics Reliability, Vol. 53, No. 6, pp. 840-847, Jun. 2013. crossref(new window)

B. Fridholm, M. Nilsson, and T. Wik, "Robustness comparison of battery state of charge observers for automotive applications⋆," in 19th World Congress, Vol. 19, No. 1, pp. 2138-2146, Aug. 2014.

X. Chen, W. Shen, Z. Cao, and A. Kapoor, "A comparative study of observer design techniques for state of charge estimation in electric vehicles,"in 7th IEEE Conference on Industrial Electronics and Applications(ICIEA), pp. 102-107, Jul. 2012.

X. Li, J. Jiang, C. Zhang, W. Zhang, and B. Sun, "Effects analysis of model parameters uncertainties on battery SOC estimation using H-infinity observer," in IEEE 23rd International Symposium on Industrial Electronics(ISIE), pp. 1647-1653, Jun. 2014.

D. D. Domenico, G. Fiengo, and A. Stefanopoulou, "Lithium-ion battery state of charge estimation with a kalman filter based on a electrochemical model," in IEEE International Conference on Control Applications(CCA), pp. 702-707, Sep. 2008.

H. He, R. Xiong, and J. Fan, “Evaluation of lithium-ion battery equivalent circuit models for state of charge estimation by an experimental approach,” Energies, Vol. 4, No. 4, pp. 582-598, Mar. 2011. crossref(new window)

F. Huet, “A review of impedance measurements for determination of the state-of-charge or state-of-health of secondary batteries,” Journal of power sources, Vol. 70, No. 1, pp. 59-69, Jan. 1998. crossref(new window)

M. Thele, O. Bohlen, D. U. Sauer, and E. Karden, “Development of a voltage-behavior model for NiMH batteries using an impedance-based modeling concept,” Journal of Power Sources, Vol. 175, No. 1, pp. 635-643, Jan. 2008. crossref(new window)

A. A. H. Hussein, N. Kutkut, and I. Batarseh, "A hysteresis model for a lithium battery cell with improved transient response," in 26th Annual IEEE Applied Power Electronics Conference and Exposition(APEC), pp. 1790-1794, Mar. 2011.

V. H. Johnson, A. A. Pesaran, and T. Sack, Temperature-dependent battery models for high-power lithium-ion batteries, City of Golden: National Renewable Energy Laboratory, pp. 1-17, 2001.

I. Petersen, V. A. Ugrinovskii, and A. V. Savkin, Robust Control Design Using H-∞ Methods, Springer Science & Business Media, Chap. 3, 2012.

J. Qiu, G. Feng, and J. Yang, “A new design of delay-dependent robust H-infinity filtering for discrete-time T-S fuzzy systems with time-varying delay,” IEEE Trans. Fuzzy Syst., Vol. 17, No. 5, pp. 1044-1058, Oct. 2009. crossref(new window)

Z. He, M. Gao, C. Wang, L. Wang, and Y. Liu, “Adaptive state of charge estimation for Li-ion batteries based on an unscented Kalman filter with an enhanced battery model,” Energies, Vol. 6, No. 8, pp. 4134-4151, Aug. 2013. crossref(new window)

Dynamometer Driving Scheules Utilized at the National Vehicle and Fuel Emissions Laboratory,, Jun. 2012.

G. Sarre, P. Blanchard, and M. Broussely, “Aging of lithium-ion batteries,” Journal of Power Sources, Vol. 127, No. 1-2, pp. 65-71, Mar. 2004. crossref(new window)