State of health estimation for lithium ion batteries based on charging curves

被引:133
|
作者
Guo, Zhen [1 ]
Qiu, Xinping [2 ]
Hou, Guangdong [1 ]
Liaw, Bor Yann [3 ]
Zhang, Changshui [1 ]
机构
[1] Tsinghua Univ, Dept Automat, TNList, State Key Lab Intelligent Technol & Syst, Beijing 100084, Peoples R China
[2] Tsinghua Univ, Dept Chem, Key Lab Organ Optoelect & Mol Engn, Beijing 100084, Peoples R China
[3] Univ Hawaii Manoa, SOEST, Hawaii Nat Energy Inst, Honolulu, HI 96822 USA
关键词
State of health; Lithium ion battery; Charge curve; Nonlinear least squares method; IDENTIFICATION; CELLS; SOC;
D O I
10.1016/j.jpowsour.2013.10.114
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
An effective method to estimate the state of health (SOH) of lithium ion batteries is illustrated in this work. This method uses an adaptive transformation of charging curves at different stages of life to quantify the extent of capacity fade and derive a time-based parameter to enable an accurate SOH estimation. This approach is easy for practical implementation and universal to chemistry or cell geometry, with minimal demand of learning. With a typical constant current-constant voltage (CC-CV) charging method for a lithium ion battery, this approach uses an equivalent circuit model to characterize the CC portion of the charging curve and derive a transformation function and a time-based parameter to estimate SOH at any stage of life via a nonlinear least squares method to identify model parameters. The SOH estimation errors (discrepancy between estimated and experimental values, denoted as Delta SOH) are under 2% before the end of life in cases shown at 25 degrees C and 60 degrees C and a range of typical discharging rates up to 3C. With different sizes and chemistries, the Delta SOHs are all less than 3%. (C) 2013 Elsevier B.V. All rights reserved.
引用
收藏
页码:457 / 462
页数:6
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