State-of-health estimation for Li-ion batteries by combing the incremental capacity analysis method with grey relational analysis

被引:311
作者
Li, Xiaoyu [1 ,2 ]
Wang, Zhenpo [1 ,2 ]
Zhang, Lei [1 ,2 ]
Zou, Changfu [3 ]
Dorrell, David. D. [4 ]
机构
[1] Beijing Inst Technol, Natl Engn Lab Elect Vehicles, Sch Mech Engn, Beijing 100081, Peoples R China
[2] Beijing Inst Technol, Collaborat Innovat Ctr Elect Vehicles Beijing, Beijing 100081, Peoples R China
[3] Chalmers Univ Technol, Dept Elect Engn, S-41296 Gothenburg, Sweden
[4] Univ KwaZulu Natal, Discipline Elect Elect & Comp Engn, ZA-4041 Durban, South Africa
基金
中国国家自然科学基金;
关键词
Lithium-ion batteries; State-of-health; Incremental capacity analysis; Grey relational analysis; Entropy weight method; ON-BOARD STATE; CHARGE ESTIMATION; DIAGNOSIS; SYSTEM; FILTER; MODEL;
D O I
10.1016/j.jpowsour.2018.10.069
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070305 [高分子化学与物理];
摘要
An accurate battery state-of-health (SOH) monitoring is crucial to guarantee safe and reliable operation of electric vehicles (EVs). In this paper, an incremental capacity analysis (ICA) method for battery SOH estimation is proposed. This uses grey relational analysis in combination with the entropy weight method. First, an interpolation method is employed to obtain incremental capacity (IC) curves. The health indexes are then extracted from the partial IC curves for grey relational analysis, and the entropy weight method is used to evaluate the significance of each health index. The battery SOH is assessed by calculating the grey relational degree between the reference and comparative sequences. Experimental tests are conducted on two battery cells with the same specifications to verify the efficacy of the proposed method. The results show that the maximum estimation error is limited to within 4%, thus proving its effectiveness.
引用
收藏
页码:106 / 114
页数:9
相关论文
共 34 条
[1]
[Anonymous], [No title captured]
[2]
Building better batteries [J].
Armand, M. ;
Tarascon, J. -M. .
NATURE, 2008, 451 (7179) :652-657
[3]
Online battery state of health estimation based on Genetic Algorithm for electric and hybrid vehicle applications [J].
Chen, Zheng ;
Mi, Chunting Chris ;
Fu, Yuhong ;
Xu, Jun ;
Gong, Xianzhi .
JOURNAL OF POWER SOURCES, 2013, 240 :184-192
[4]
Environmental conflict analysis using an integrated grey clustering and entropy-weight method: A case study of a mining project in Peru [J].
Delgado, Alexi ;
Romero, I. .
ENVIRONMENTAL MODELLING & SOFTWARE, 2016, 77 :108-121
[5]
Identifying battery aging mechanisms in large format Li ion cells [J].
Dubarry, Matthieu ;
Liaw, Bor Yann ;
Chen, Mao-Sung ;
Chyan, Sain-Syan ;
Han, Kuo-Chang ;
Sie, Wun-Tong ;
Wu, She-Huang .
JOURNAL OF POWER SOURCES, 2011, 196 (07) :3420-3425
[6]
Using probability density function to evaluate the state of health of lithium-ion batteries [J].
Feng, Xuning ;
Li, Jianqiu ;
Ouyang, Minggao ;
Lu, Languang ;
Li, Jianjun ;
He, Xiangming .
JOURNAL OF POWER SOURCES, 2013, 232 :209-218
[7]
Lithium-ion battery aging mechanisms and life model under different charging stresses [J].
Gao, Yang ;
Jiang, Jiuchun ;
Zhang, Caiping ;
Zhang, Weige ;
Ma, Zeyu ;
Jiang, Yan .
JOURNAL OF POWER SOURCES, 2017, 356 :103-114
[8]
A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations [J].
Hannan, M. A. ;
Lipu, M. S. H. ;
Hussain, A. ;
Mohamed, A. .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2017, 78 :834-854
[9]
Hu XS, 2011, P AMER CONTR CONF, P935
[10]
Klir G. J., 1987, FUZZY SETS UNCERTAIN, P355