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Li-ion battery capacity estimation: A geometrical approach

  • Chen Lu
  • , Laifa Tao*
  • , Huanzhen Fan
  • *Corresponding author for this work
  • Beihang University
  • Science & Technology on Reliability & Environmental Engineering Laboratory
  • University of Cincinnati
  • CASIC

Research output: Contribution to journalArticlepeer-review

Abstract

The majority of methods used for lithium-ion (Li-ion) capacity estimation are usually restricted to certain applications. Such methods often are time consuming and inconsistent with actual experimental data as well as depending on complicated battery operating and/or aging conditions. A geometrical approach to Li-ion battery capacity estimation is presented in this work. The proposed method utilizes four geometrical features that are sensitive to slight changes in the performance degradation of a Li-ion battery. The Laplacian Eigenmap method is used to establish an intrinsic manifold, and the geodesic on the manifold is used to estimate battery capacity. Tests are conducted based on data obtained under different operating and aging conditions provided by NASA Prognostics Center of Excellence. The evaluation results suggest that the proposed geometrical approach can be used to estimate Li-ion battery capacity accurately for the conditions given in this article.

Original languageEnglish
Pages (from-to)141-147
Number of pages7
JournalJournal of Power Sources
Volume261
DOIs
StatePublished - 1 Sep 2014

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Capacity estimation
  • Geometrical approach
  • Lithium ion battery
  • Manifold learning

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