电池(电)
降级(电信)
计算机科学
鉴定(生物学)
锂离子电池
可靠性工程
桥(图论)
工程类
功率(物理)
植物
量子力学
医学
电信
生物
物理
内科学
作者
David Anseán,Víctor M. García,Miguel Ángel Álvarez González,Cecilio Blanco-Viejo,J.C. Viera,Yoana Fernández Pulido,Luciano Sánchez
出处
期刊:IEEE Transactions on Industry Applications
[Institute of Electrical and Electronics Engineers]
日期:2019-05-01
卷期号:55 (3): 2992-3002
被引量:125
标识
DOI:10.1109/tia.2019.2891213
摘要
Lithium-ion battery (LIB) degradation originates from complex mechanisms, usually interacting simultaneously in various degrees of intensity. Due to its complexity, to date, identifying battery aging mechanisms remains challenging. Recent improvements in battery degradation identification have been developed, including validated, in situ incremental capacity (IC) and peak area (PA) analysis. Due to their in situ and non-destructive nature, IC and PA implementation is feasible in on-board battery management systems (BMSs). Despite their advantages, the understanding and applicability of IC and PA techniques is not straightforward, as it requires both electrochemical and material science backgrounds. However, BMS design teams are mainly integrated by electrical engineers and may not include battery scientists. Aiming to bridge gaps in knowledge between electrical engineering and battery science toward battery degradation identification, here we present a systematic approach consisting in a set of lookup tables generated from IC and PA techniques. The lookup tables provide a simple, yet reliable, tool for the evaluation of LIB degradation modes. Various real-life examples of cell degradation are also presented to illustrate and validate the use of the proposed approach. This study exemplifies the use of lookup tables providing a simple, fast, and accurate automated estimation of LIB degradation modes to be implemented in BMSs.
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