Abstract
An accurate state of charge (SOC) estimation is the basis of the Battery Management System (BMS). In this paper, a new estimation method which considers fractional calculus is proposed to estimate the lithium battery state of charge. Firstly, a modified second-order RC model based on fractional calculus theory is developed to model the lithium battery characteristics. After that, a pulse characterization test is implemented to obtain the battery terminal voltage and current, in which the parameter identification is completed based on least square method. Furthermore, the proposed method based on Fractional Unscented Kalman Filter (FUKF) algorithm is applied to estimate the battery state of charge value in both static and dynamic battery discharging experiment. The experimental results have demonstrated that the proposed method shows high accuracy and efficiency for state of charge estimation and the fractional calculus contributes to the battery state of charge estimation.
Highlights
In response to the concerns of the energy depleting and environment protection, electric vehicles and hybrid electric vehicles are proposed as popular substitutions for conventional fossil fuel vehicles for a wide range [1]
Fractional Unscented Kalman Filter (FUKF) is based on unscented transformation which approximates the probability distribution of the variable by using sigma points [34]
With the voltage and current curves of the pulse characterization experiment, the seven unknown parameters can be determined and this is the previous work of the battery state of charge (SOC) estimation with FUKF
Summary
In response to the concerns of the energy depleting and environment protection, electric vehicles and hybrid electric vehicles are proposed as popular substitutions for conventional fossil fuel vehicles for a wide range [1]. Liu et al established a fractional-order PNGV model and Extended Fractional Kalman Filter (EFKF) to implement the state estimation [26]. These scholars have proved that fractional calculus is capable of accurately depicting system performance in real system. Considering the advantages of UKF in contrast to KF and EKF in integer systems mentioned above, it is reasonable and practicable to combine fractional calculus with UKF to propose a new method, which may be useful for battery SOC estimation accuracy. The main contributions of this paper are: (1) developing an equivalent second-order resistance-capacitance (RC) circuit model with fractional operator; (2) developing a UKF algorithm combined with fractional calculus to estimate the battery SOC.
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