A New State of Charge Estimation Method for Lithium-Ion Battery Based on the Fractional Order Model
Shulin Liu, Xia Dong, Yun Zhang
IEEE Access · 2019
doi:10.1109/access.2019.2932142 (opens in a new tab)
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Abstract
This paper presents that the fractional order Kalman filter (FOKF) method is used to estimate the state of charge (SOC) for lithium-ion battery based on the fractional order model. First, a fractional order battery model was established which can better reflect the dynamic characteristics of the battery. The fractional orders were identified by genetic algorithm. Then, compared with three other modeling methods in four aspects: maximum absolute error, maximum relative error, computational complexity and number of model parameters, it is shown that the fractional order model proposed in this paper is more accurate and reliable. The results shows that the maximum absolute error of the terminal voltage is 0.014 V under constant current discharge test. The accuracy improves 0.058 V comparing to the integer order model. Finally, the SOC was estimated through two methods. The results shows that the maximum absolute estimation error of SOC is under 0.02 by FOKF, which has higher accuracy and faster convergence speed compared with extend Kalman filter (EKF) method.
Abstract licence: CC BY-NC-ND
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