State-of-Charge Estimation of Lithium-Ion Batteries Based on Fractional-Order Square-Root Unscented Kalman Filter

被引：11
|
作者：
Chen, Liping [1 ]
Wu, Xiaobo [1 ]
Tenreiro Machado, Jose A. [2 ]
Lopes, Antonio M. [3 ]
Li, Penghua [4 ]
Dong, Xueping [1 ]
机构：
[1] Hefei Univ Technol, Sch Elect Engn & Automat, Hefei 230009, Peoples R China
[2] Polytech Porto, Inst Engn, Dept Elect Engn, Rua Dr Antonio Bernardino Almeida 431, P-4249015 Porto, Portugal
[3] Univ Porto, Fac Engn, INEGI, UISPA LAETA, Rua Dr Roberto Frias, P-4200465 Porto, Portugal
[4] Chongqing Univ Posts & Telecommun, Coll Automat, Automot Elect Engn Res Ctr, Chongqing 400065, Peoples R China
来源：
FRACTAL AND FRACTIONAL | 2022年 / 6卷 / 02期
关键词：
state-of-charge estimation; fractional-order equivalent circuit; square-root unscented Kalman filter; EQUIVALENT-CIRCUIT MODELS; ESTIMATION ALGORITHM; MANAGEMENT-SYSTEM; SOC;
D O I：
10.3390/fractalfract6020052
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
The accuracy of the state-of-charge (SOC) estimation of lithium batteries affects the battery life, driving performance, and the safety of electric vehicles. This paper presents a SOC estimation method based on the fractional-order square-root unscented Kalman filter (FSR-UKF). Firstly, a fractional second-order Resistor-Capacitance (RC) circuit model of the lithium battery is derived. The accuracy of the parameterized model is verified, revealing its superiority over integer-order standard descriptions. Then, the FSR-UKF algorithm is developed, combining the advantages of the square-root unscented Kalman filter and the fractional calculus. The effectiveness of the proposed algorithm is proven under a variety of operational conditions in the perspective of the root-mean-squared error, which is shown to be below <mml:semantics>1.0%</mml:semantics>. In addition, several experiments illustrate the performance of the FSR-UKF.
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收藏
页数：20
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