电池(电)
降级(电信)
计算机科学
锂离子电池
桥(图论)
可靠性工程
锂(药物)
关系(数据库)
工程类
功率(物理)
数据挖掘
电信
医学
物理
内科学
内分泌学
量子力学
作者
David Anseán,M. González,Cecilio Blanco,J.C. Viera,Yoana Fernández Pulido,V. Fernandez
标识
DOI:10.1109/eeeic.2017.7977776
摘要
Lithium ion battery (LIB) degradation originates from complex mechanisms, usually interacting simultaneously, and in various degrees of intensity. Due to its complexity, to date, identifying battery aging mechanisms remains challenging. To resolve such issue, various techniques have been developed, including in-situ incremental capacity (IC) and peak area (PA) analysis. The use of these techniques has been proved to be valuable for identifying LIB degradation, both qualitatively and quantitatively. In addition, due to their in-situ and non-destructive nature, the implementation of these techniques is feasible for onboard, battery management systems (BMS). However, the understanding and direct applicability of IC and PA techniques is not straightforward, as it requires the understanding of electrochemical and material science principles. Unfortunately, BMS design teams rarely include battery scientists, and are mainly composed of electrical engineers. Aiming to bridge gaps in knowledge between electrical engineering and battery science, here we present a set of direct look-up tables generated from IC analysis, that provides a simple tool for the evaluation of LIB degradation modes. We begin with a brief overview of the basics of IC and PA techniques and their relation to battery degradation modes, to later present the look-up tables, and conclude with various real-life examples of cell degradation, to illustrate the use of the look-up tables. This study exemplifies the use of look-up tables for BMS applications, providing a simple, fast and accurate real-time estimation of LIB degradation modes.
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