Comparisons of Modeling and State of Charge Estimation for Lithium-Ion Battery Based on Fractional Order and Integral Order Methods

Renxin Xiao, Jiangwei Shen, Xiaoyu Li, Wensheng Yan, Erdong Pan and Zheng Chen
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Renxin Xiao: Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650500, China
Jiangwei Shen: Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650500, China
Xiaoyu Li: Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650500, China
Wensheng Yan: Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650500, China
Erdong Pan: Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650500, China
Zheng Chen: Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650500, China

Energies, 2016, vol. 9, issue 3, 1-15

Abstract: In order to properly manage lithium-ion batteries of electric vehicles (EVs), it is essential to build the battery model and estimate the state of charge (SOC). In this paper, the fractional order forms of Thevenin and partnership for a new generation of vehicles (PNGV) models are built, of which the model parameters including the fractional orders and the corresponding resistance and capacitance values are simultaneously identified based on genetic algorithm (GA). The relationships between different model parameters and SOC are established and analyzed. The calculation precisions of the fractional order model (FOM) and integral order model (IOM) are validated and compared under hybrid test cycles. Finally, extended Kalman filter (EKF) is employed to estimate the SOC based on different models. The results prove that the FOMs can simulate the output voltage more accurately and the fractional order EKF (FOEKF) can estimate the SOC more precisely under dynamic conditions.

Keywords: fractional order model; extended Kalman filter; genetic algorithm; lithium-ion battery; parameters identification; state of charge (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

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