A review on prognostics and health monitoring of Li-ion battery

被引:620
作者
Zhang, Jingliang [1 ]
Lee, Jay [1 ]
机构
[1] Univ Cincinnati, Dept Mech Engn, Ctr Intelligent Maintenance Syst, Cincinnati, OH 45221 USA
关键词
Prognostics; Health monitoring; Li-ion battery; Estimation; Prediction; RUL; STATE-OF-CHARGE; LEAD-ACID-BATTERIES; MANAGEMENT-SYSTEMS; MODEL; PACKS;
D O I
10.1016/j.jpowsour.2011.03.101
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
The functionality and reliability of Li-ion batteries as major energy storage devices have received more and more attention from a wide spectrum of stakeholders, including federal/state policymakers, business leaders, technical researchers, environmental groups and the general public. Failures of Li-ion battery not only result in serious inconvenience and enormous replacement/repair costs, but also risk catastrophic consequences such as explosion due to overheating and short circuiting. In order to prevent severe failures from occurring, and to optimize Li-ion battery maintenance schedules, breakthroughs in prognostics and health monitoring of Li-ion batteries, with an emphasis on fault detection, correction and remaining-useful-life prediction, must be achieved. This paper reviews various aspects of recent research and developments in Li-ion battery prognostics and health monitoring, and summarizes the techniques, algorithms and models used for stale-of-charge (SOC) estimation, current/voltage estimation, capacity estimation and remaining-useful-life (RUL) prediction. (C) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码:6007 / 6014
页数:8
相关论文
共 43 条
[1]  
[Anonymous], 2009, MODELING LI ION BATT
[2]  
[Anonymous], 2008, 2008 ANN PROGR REP E
[3]  
BIAGETTI RV, 1990, APPARATUS METHOD ADA
[4]  
BISHOP CM, 2006, PATTERN RECOGN, P433
[5]   Impedance measurements on lead-acid batteries for state-of-charge, state-of-health and cranking capability prognosis in electric and hybrid electric vehicles [J].
Blanke, H ;
Bohlen, O ;
Buller, S ;
De Doncker, RW ;
Fricke, B ;
Harnmouche, A ;
Linzen, D ;
Thele, M ;
Sauer, DU .
JOURNAL OF POWER SOURCES, 2005, 144 (02) :418-425
[6]  
BRILMYER GH, 1989, DYNAMIC STATE OF CHA
[7]   The available capacity computation model based on artificial neural network for lead-acid batteries in electric vehicles [J].
Chan, CC ;
Lo, EWC ;
Shen, WX .
JOURNAL OF POWER SOURCES, 2000, 87 (1-2) :201-204
[8]  
CHIASSERINI C, 1999, P 5 ANN ACM IEEE INT, P95
[9]   SIMULATION AND OPTIMIZATION OF THE DUAL LITHIUM ION INSERTION CELL [J].
FULLER, TF ;
DOYLE, M ;
NEWMAN, J .
JOURNAL OF THE ELECTROCHEMICAL SOCIETY, 1994, 141 (01) :1-10
[10]  
*GAMR INSTR, 2010, EL IMP SPECTR THEOR