A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
Volume 3 Issue 3
Jul.  2016

IEEE/CAA Journal of Automatica Sinica

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Article Contents
Yan Ma, Xiuwen Zhou, Bingsi Li and Hong Chen, "Fractional Modeling and SOC Estimation of Lithium-ion Battery," IEEE/CAA J. of Autom. Sinica, vol. 3, no. 3, pp. 281-287, 2016.
Citation: Yan Ma, Xiuwen Zhou, Bingsi Li and Hong Chen, "Fractional Modeling and SOC Estimation of Lithium-ion Battery," IEEE/CAA J. of Autom. Sinica, vol. 3, no. 3, pp. 281-287, 2016.

Fractional Modeling and SOC Estimation of Lithium-ion Battery


This work was supported by National Natural Science Foundation of China (615 20106008, U1564207, 61503149), High Technology Research and Development Program of Jilin (20130204021GX), Specialized Research Fund for Graduate Course Identification System Program (Jilin University) of China (450060523183), and Graduate Innovation Fund of Jilin University (20151 48).

  • This paper proposes a state of charge (SOC) estimator of Lithium-ion battery based on a fractional order impedance spectra model. Firstly, a battery fractional order impedance model is derived on the grounds of the characteristics of Warburg element and constant phase element (CPE) over a wide range of frequency domain. Secondly, a frequency fitting method and parameter identification algorithm based on output error are presented to identify parameters of the fractional order model of Lithium-ion battery. Finally, the fractional order Kalman filter approach is introduced to estimate the SOC of the lithium-ion battery based on the fractional order model. The simulation results show that the fractional-order model can ensure an acceptable accuracy of the SOC estimation, and the error of estimation reaches maximally up to 0.5% SOC.


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