基于恒流外特性和SOC的电池直流内阻测试方法

何志超, 杨耕, 卢兰光, 吴海桑

清华大学学报（自然科学版） ›› 2015, Vol. 55 ›› Issue (5) : 532-537.

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清华大学学报（自然科学版） ›› 2015, Vol. 55 ›› Issue (5) : 532-537.
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基于恒流外特性和SOC的电池直流内阻测试方法

  • 何志超1, 杨耕1, 卢兰光2, 吴海桑1
作者信息 +

Battery DC internal resistance test method based on the constant current external characteristics and SOC

  • HE Zhichao1, YANG Geng1, LU Languang2, Wu Haisang1
Author information +
文章历史 +

摘要

电池的直流内阻是电池内部离子电阻与电子电阻之和。它决定电池功率特性, 同时也反映电池的老化状况与一致性, 因此对于电池的外特性建模与应用非常重要。该文提出了一种基于电池恒流外特性的直流内阻测试方法。该方法将不同恒流工况下的电池荷电状态(state of charge, SOC)变化过程归一化, 从而能够利用恒流充放电曲线来获取不同工作电流及SOC条件下的直流内阻。该方法在保证测试精度的同时比已有方法更加简便。

Abstract

The direct current internal resistance (DCIR) is the sum of a battery's ionic and electronic resistances. The DCIR test indicates the battery's power characteristics and reflects the batteries' aging and uniformity characteristics. Thus, it is important for battery modeling and applications. This paper describes a DCIR test method based on the battery's constant current external characteristics. This method normalizes the battery's state of charge (SOC) changes for different constant current conditions. Then, the DCIR for different operating currents and SOC are obtained using constant current charge/discharge curves. This method is easier to implement than existing methods and has good accuracy.

关键词

锂离子电池 / 直流内阻 / 恒流外特性 / 荷电状态

Key words

lithium-ion battery / direct current internal resistance (DCIR) / constant current external characteristics / state of charge (SOC)

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何志超, 杨耕, 卢兰光, 吴海桑. 基于恒流外特性和SOC的电池直流内阻测试方法[J]. 清华大学学报（自然科学版）. 2015, 55(5): 532-537
HE Zhichao, YANG Geng, LU Languang, Wu Haisang. Battery DC internal resistance test method based on the constant current external characteristics and SOC[J]. Journal of Tsinghua University(Science and Technology). 2015, 55(5): 532-537
中图分类号： TQ152    TP29   

参考文献

[1] Linden D. Handbook of Batteries [M]. 3rd ED. New York, NY, USA: McGraw-Hill, 2001.
[2] Carter R, Cruden A, Hall P, et al. An improved lead–acid battery pack model for use in power simulations of electric vehicles [J]. IEEE Transactions on Energy Conversion, 2012, 27(1): 21-28.
[3] Gould C, Bingham C, Stone D, et al. New battery model and state-of-health determination through subspace parameter estimation and state-observer techniques [J]. IEEE Transactions on Vehicular Technology, 2009, 58(8): 3905-3916.
[4] Lu L, Han X, Li J, et al. A review on the key issues for lithium-ion battery management in electric vehicles [J]. Journal of Power Sources, 2012, 226: 272-288.
[5] He H, Xiong R, Fan J. Evaluation of lithium-ion battery equivalent circuit models for state of charge estimation by an experimental approach [J]. Journal of Energies, 2011, 4: 582-598.
[6] Hu X, Li S, Peng H. Comparative study of equivalent circuit models for Li-ion batteries [J]. Journal of Power Sources, 2012, 198: 359-367.
[7] Szumanowski A, Chang Y. Battery management system based on battery nonlinear dynamics modeling [J]. IEEE Transactions on Vehicular Technology, 2008, 57(3): 1425-1432.
[8] Chen S, Gooi H, Xia N, et al. Modelling of lithium-ion battery for online energy management systems [J]. IET Electrical Systems in Transportation, 2012, 2(4): 202-210.
[9] DOE/ID-10597. PNGV Battery Test Manual Revision 3 [S]. Washington DC, USA: U.S. Department of Energy, 2001.
[10] Zhao S, Wu F, Yang L, et al. A measurement method for determination of DC internal resistance of batteries and supercapacitors [J]. Electrochemistry Communications, 2010, 12: 242-245.
[11] Remmlinger J, Buchholz M, Meiler M. State-of-health monitoring of lithium-ion batteries in electric vehicles by on-board internal resistance estimation [J]. Journal of Power Sources, 2011, 196: 5357-5363.
[12] 林成涛,王军平,陈全世. 电动汽车SOC估计方法原理与应用 [J]. 电池,2004,34(5):376-278.LIN Chengtao, WANG Junping, CHEN Quanshi.Methods for state of charge estimation of EV batteries and their application [J]. Batteries, 2004, 34(5): 376-378. (in Chinese)
[13] Piller S, Perrin M, Jossen A. Methods for state of charge determination and their applications [J]. Journal of Power Sources, 2001, 96: 113-120.
[14] adirci Y, zkazanY. Microcontroller-based on-line state-of-charge estimator for sealed lead–acid batteries [J]. Journal of Power Sources, 2004, 129: 330-342.
[15] Doerffel D, Sharkh S. A critical review of using the Peukert equation for determining the remaining capacity of lead-acid and lithium-ion batteries [J]. Journal of Power Sources, 2006, 155: 395-400.
[16] Coleman M, Lee C K, Zhu C, et al. State-of-charge determination from EMF voltage estimation: using impedance, terminal voltage, and current for lead-acid and lithium-ion batteries [J]. IEEE Transactions on Industrial Electronics, 2007, 54(5): 2550-2557.
[17] Bard A J, Faulkner L R. Electrochemical Methods Fundamentals and Applications [M]. New York, NY, USA: John Wiley & Sons Inc., 2001.
[18] 林成涛, 张宾, 陈全世, 等. 典型动力电池特性与性能的对比研究 [J]. 电源技术,2008,32(11):735-738.LIN Chengtao, ZHANG Bin, CHEN Quanshi, et al.Comparative research on characteristics and performance of typical tractive battery [J]. Chinese Journal of Power Sources, 2008, 32(11): 735-738. (in Chinese)
[19] 李哲, 韩雪冰, 卢兰光, 等. 动力型磷酸铁锂电池的温度特性 [J]. 机械工程学报,2011, 47(18):115-120.LI Zhe, HAN Xuebing, LU Languang, et al.Temperature characteristics of power lifepo4 batteries [J]. Journal Of Mechanical Engineering, 2011, 47(18): 115-120. (in Chinese)
[20] Ouyang M, Liu G, Lu L, et al. Enhancing the estimation accuracy in low state-of-charge area: A novel onboard battery model through surface state of charge determination [J]. Journal of Power Sources, 2014, 270: 221-237.

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