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

被引:606
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
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