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Online State of Charge Estimation for Battery in Electric Vehicles Based on Forgetting Factor Recursive Least Squares
Received date: 2019-09-29
Online published: 2020-12-31
An advanced battery management system ensures the safe and efficient use of batteries in electric vehicles. As the state of charge (SOC) cannot be measured directly, it is important for the battery management system to accurately and reliably estimate the SOC of batteries. In order to estimate SOC, a first-order resistor-capacitance (RC) equivalent circuit model is used to describe the external characteristic of batteries. The model parameters are identified by forgetting factor recursive least-squares (FFRLS). Open circuit voltage (OCV) is one of the model parameters, and then SOC can be estimated by the SOC-OCV model. The CALCE battery research group in the University of Maryland has proposed some data, which include the data of LNMC/graphite battery working under dynamic stress test (DST) and Beijing dynamic stress test (BJDST) conditions. These data are used to verify the proposed algorithm. The results show that the estimation error does not exceed 3.419 0% in DST and 4.233 5% in BJDST, which indicates that the proposed method can realize online SOC estimation.
CHEN Yushan, QIN Linlin, WU Gang, MAO Junxin . Online State of Charge Estimation for Battery in Electric Vehicles Based on Forgetting Factor Recursive Least Squares[J]. Journal of Shanghai Jiaotong University, 2020 , 54(12) : 1340 -1346 . DOI: 10.16183/j.cnki.jsjtu.2020.172
| [1] | XING Y J, HE W, PECHT M, et al. State of charge estimation of lithium-ion batteries using the open-circuit voltage at various ambient temperatures[J]. Applied Energy, 2014, 113: 106-115. |
| [2] | LAI X, ZHENG Y J, SUN T. A comparative study of different equivalent circuit models for estimating state-of-charge of lithium-ion batteries[J]. Electrochimica Acta, 2018, 259: 566-577. |
| [3] | TANIM T R, RAHN C D, WANG C Y. State of charge estimation of a lithium ion cell based on a temperature dependent and electrolyte enhanced single particle model[J]. Energy, 2015, 80: 731-739. |
| [4] | LU L G, HAN X B, LI J Q, et al. A review on the key issues for lithium-ion battery management in electric vehicles[J]. Journal of Power Sources, 2013, 226: 272-288. |
| [5] | XIONG R, SUN F C, GONG X Z, et al. A data-driven based adaptive state of charge estimator of lithium-ion polymer battery used in electric vehicles[J]. Applied Energy, 2014, 113: 1421-1433. |
| [6] | HE W, WILLIARD N, CHEN C, et al. State of charge estimation for Li-ion batteries using neural network modeling and unscented Kalman filter-based error cancellation[J]. International Journal of Electrical Power and Energy Systems, 2014, 62: 783-791. |
| [7] | WANG Y J, ZHANG C B, CHEN Z H. On-line battery state-of-charge estimation based on an integrated estimator[J]. Applied Energy, 2017, 185: 2026-2032. |
| [8] | YANG F F, XING Y J, WANG D, et al. A comparative study of three model-based algorithms for estimating state-of-charge of lithium-ion batteries under a new combined dynamic loading profile[J]. Applied Energy, 2016, 164: 387-399. |
| [9] | DUONG V H, BASTAWROUS H A, LIM K, et al. Online state of charge and model parameters estimation of the LiFePO4 battery in electric vehicles using multiple adaptive forgetting factors recursive least-squares[J]. Journal of Power Sources, 2015, 296: 215-224. |
| [10] | HE H W, ZHANG X W, XIONG R, et al. Online model-based estimation of state-of-charge and open-circuit voltage of lithium-ion batteries in electric vehicles[J]. Energy, 2012, 39(1): 310-318. |
| [11] | ZHANG C, ALLAFI W, DINH Q, et al. Online estimation of battery equivalent circuit model parameters and state of charge using decoupled least squares technique[J]. Energy, 2018, 142: 678-688. |
| [12] | PALEOLOGU C, BENESTY J, CIOCHINA S. A robust variable forgetting factor recursive least-squares algorithm for system identification[J]. IEEE Signal Processing Letters, 2008, 15: 597-600. |
| [13] | 冯培悌. 系统辨识[M]. 2版. 杭州： 浙江大学出版社，2004. |
| [13] | FENG Peiti. System identification [M]. 2nd ed. Hangzhou: Zhejiang University Press, 2004. |
| [14] | ZHENG F D, XING Y J, JIANG J C, et al. Influence of different open circuit voltage tests on state of charge online estimation for lithium-ion batteries[J]. Applied Energy, 2016, 183: 513-525. |
| [15] | DUONG T Q. USABC and PNGV test procedures[J]. Journal of Power Sources, 2000, 89(2): 244-248. |
| [16] | 时玮，姜久春，张维戈，等. 纯电动公交车动力电池寿命测试行驶工况的研究[J]. 汽车工程，2013, 35(2): 138-151. |
| [16] | SHI Wei, JIANG Jiuchun, ZHANG Weige, et al. A study on the driving cycle for the life test of traction battery in electric buses[J]. Automotive Engineering, 2013, 35(2): 138-151. |
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