Remaining useful life predictions in lithium-ion battery under composite condition

Yejin Kim, Jongsoo Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In these days, there is a tendency that research of Prognostics and Health Management (PHM) of lithium-ion battery that prevent accidents in advance by predicting the Remaining Useful Life (RUL). However, there is a difficulty in battery evaluation for composite condition of an operating conditions and a storage conditions, due to the time consuming. Research on the RUL of lithium-ion battery in composite condition are progressing by combining an operating condition and a storage condition. Conventional method such as Miner's Rule may not fully meet the needs of battery evaluation for RUL. Because it does not take into account overloads caused by a variable amplitude loading history. In order to solve the problem of accurately predicting the RUL of lithium-ion battery, two approaches applied to predicting the RUL of lithium-ion battery. We demonstrate the usefulness of two proposed methods by comparing with real-data of composite condition.

Original languageEnglish
Title of host publicationPHM 2016 - Proceedings of the Annual Conference of the Prognostics and Health Management Society
EditorsMatthew J. Daigle, Anibal Bregon
PublisherPrognostics and Health Management Society
Pages363-369
Number of pages7
ISBN (Electronic)9781936263059
Publication statusPublished - 2016
Event2016 Annual Conference of the Prognostics and Health Management Society, PHM 2016 - Denver, United States
Duration: 2016 Oct 32016 Oct 6

Publication series

NameProceedings of the Annual Conference of the Prognostics and Health Management Society, PHM
Volume2016-October
ISSN (Print)2325-0178

Other

Other2016 Annual Conference of the Prognostics and Health Management Society, PHM 2016
CountryUnited States
CityDenver
Period16/10/316/10/6

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Electrical and Electronic Engineering
  • Health Information Management
  • Computer Science Applications

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  • Cite this

    Kim, Y., & Lee, J. (2016). Remaining useful life predictions in lithium-ion battery under composite condition. In M. J. Daigle, & A. Bregon (Eds.), PHM 2016 - Proceedings of the Annual Conference of the Prognostics and Health Management Society (pp. 363-369). (Proceedings of the Annual Conference of the Prognostics and Health Management Society, PHM; Vol. 2016-October). Prognostics and Health Management Society.