IEEE Transactions on Industrial Electronics, Vol. 66, Issue 9, September 2019 DOI: 10.1109/TIE.2018.2880701

Reduction of Li-ion Battery Qualification Time Based on Prognostics and Health Management

Jinwoo Lee 1, Daeil Kwon 2, and Michael Pecht 3
1 School of Mechanical, Aerospace, and Nuclear Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
2 Department of Mechanical Engineering, Konkuk University, Seoul, South Korea
3 CALCE, Center for Advanced Life Cycle Engineering, Department of Mechanical Engineering, University of Maryland, College Park, Maryland 20740, USA


Lithium-ion (Li-ion) batteries have been used in a wide variety of applications, ranging from portable electronics to electric vehicles. During repetitive charging and discharging, a battery's capacity fades due to electrochemical reactions such as solid electrolyte interphase growth. Li-ion batteries reach an end-of-life (EOL) point, after which using them is not recommended. However, some unhealthy batteries reach their EOL sooner than expected. A qualification test is usually conducted to evaluate the reliability of Li-ion batteries and classify unhealthy batteries, but this test requires several months. This paper develops a data-driven method to reduce the qualification time by detecting anomalies before EOL. This method detects an anomaly in the capacity fade curve of unhealthy batteries based on their capacity fade trend. Since the developed method detects anomalies of unhealthy batteries before EOL, the method is effective in reducing the time for the qualification test of Li-ion batteries.

This article is available online here and to CALCE Consortium Members for personal review.

[Home Page] [Articles Page]
Copyright © 2019 by CALCE and the University of Maryland, All Rights Reserved