基于开路电压回升速率和交流阻抗相结合的一种锂离子电池SOH算法
收稿日期: 2013-12-01
修回日期: 2014-02-18
网络出版日期: 2014-02-28
基金资助
广东省创新团队项目（2011N071）；广东省发改委项目（粤发改高技术〔2012〕830号）；容桂镇产学研项目（容桂经发〔2013〕11号）
SOH Estimation of Li-ion Batteries by Combining Recovery Rate of Open Circuit Voltage with Impedance
Received date: 2013-12-01
Revised date: 2014-02-18
Online published: 2014-02-28
本研究所述SOH（State-of-health）估算方法是通过记录锂离子动力电池放电截止之后的开路电压值的变化，从而得出开路电压回升速率，作为主要因素判断值；对锂离子动力电池进行交流阻抗测试，得出交流阻抗图谱，并进行拟合，从而计算出锂离子动力电池的内部阻抗值，作为次要因素判断值，将主要因素判断值和次要因素判断值相加即为锂离子动力电池的SOH值，使得计算结果更加准确。该方法中考虑了电池温度、放电电流、放电截止电压等因素，得到锂离子动力电池开路电压回升曲线及内部各部分阻值。比较研究表明：该方法能够简便、快速地估算出锂离子动力电池的健康状态。
黄伟昭 , 李小平 , 张栋省 , 刘燕林 , 刘震 , 李伟善 . 基于开路电压回升速率和交流阻抗相结合的一种锂离子电池SOH算法[J]. 新能源进展, 2014 , 2(1) : 43 -48 . DOI: 10.3969/j.issn.2095-560X.2014.01.008
The estimation of SOH (State-of-health) is based on measuring the recovery rate of open circuit voltage and impedance of the lithium ion battery after discharge. The recovery rate of open circuit voltage is selected as the main factor, while the impedance as the secondary factor for the SOH estimation with considering the effects of temperature, discharge current, cut-off voltage, and various impedances in battery. This estimation is more accurate than the estimation based on a single factor.
[1] 徐保伯, 刘务华. 锂离子电池的制造及其市场[J]. 电池, 2002, 32(4): 243-244.
[2] 李伟善. 储能锂离子电池关键材料研究进展[J]. 新能源进展, 2013, 1(1): 95-105.
[3] 廖晓军, 向莉萍, 钟志华, 等. 电池管理系统国内外现状及其未来发展趋势[J]. 汽车工程, 2006, 28(10): 961-964.
[4] 雷晶晶, 李秋红, 陈立宝, 等. 动力锂离子电池管理系统的研究进展[J]. 电源技术, 34(11): 1193-1196.
[5] Gomadam P M, Weidner J W, Dougal R A, et al. Mathematical modeling of lithium-ion and nickel battery systems[J]. Journal of Power Sources, 2002, 110: 267-284.
[6] Remmlinger J, Buchholz M, Meiler M, et al. State-of-health monitoring of lithium-ion batterys in electric vehicles by on-board internal resistance estimation[J]. Journal of Power Source 2001, 1969(12): 5357-5363.
[7] Gould C R, Bingham C M, Stone D A, Bentley P. Battery health determination by subspace parameter estimation and sliding mode control for an all-electric personal rapid transit vehicle-the ultra[C]//Power Electronic Specialists Conference. Rhodes: IEEE, 2008: 4381-4385.
[8] 许参, 李杰, 王超. 一种锂离子电池寿命的预测模型[J]. 应用科学学报, 2006, 34(4): 368-371.
[9] 徐文静. 纯电动汽车锂动力电池健康状态估算方法研究[D]. 长春：吉林大学, 2012. 27-33.
[10] Gu Y L. Study of impedance model of lithium-ion battery[D]. Master Thesis of Harbin University of Science and Technology, 2008.
[11] Cao C N, Zhang J Q. Introduction of EIS[M]. Beijing: Science Press, 2002, 1-146.
[12] Wang H Y, He L, Sun J H. Study on correlation with SOH and EIS model of li-ion battery[J]. The 6th International Forum Strategic Technology, 2011: 261-264.
[13] 徐睿. 锂离子电池恶化程度与阻抗模型相关性研究[D]. 哈尔滨：哈尔滨理工大学, 2010. 11-26.
[14] 曹楚南, 张鉴清. 电化学阻抗谱导论[M]. 北京: 科学出版社, 2002. 1-40.
[15] Mingant R, Bernard J, Sauvant-Moynot V, et al. EIS measurements for determining the SOC and SOH of li-ion batteries[J]. ECS Transcations, 2011, 33(39): 41-53.
[16] Rodrigues S, Munichandraiah N, Shukla A K. A review of state-of-charge indication of battrries by means of a.c. impedance measurements[J]. Journal of Power Sources, 2000, 87: 12-20.
[17] 魏学哲, 徐玮, 沈丹. 锂离子电池内阻辨识及其在寿命估计中的应用[J]. 电源技术, 2009, 33(3): 217-220.
[18] 李伟善, 邱仕洲. 锂离子电池容量衰减的原因分析[J]. 电池工业, 2001, 6(1): 21-24.
[19] 顾帅, 韦莉, 张逸成, 等. 超级电容器老化特征与寿命测试研究展望[J]. 中国电机工程学报, 2013, 33(21): 145-153.
[20] Singh P, Vinjamuri R, Wang X Q, et al. Fuzzy logic modeling of EIS measurements on lithium-ion batteries[J]. Electrochimica Acta, 2006, 51: 1673-1679.
[21] Huet F. A review of impedance measurements for determination of the state-of-charge or state-of-health of secondary batteries[J]. Journal of Power Sources, 1998, 70: 59-69.
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