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Semi-empirical capacity fading model for SoH estimation of Li-ion batteries

  • Preetpal Singh
  • , Che Chen
  • , Cher Ming Tan*
  • , Shyh Chin Huang
  • *Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

80 Scopus citations

Abstract

A fast and accurate capacity estimation method for lithium-ion batteries is developed. This method applies our developed semi-empirical model to a discharge curve of a lithium-ion battery for the determination of its maximum stored charge capacity after each discharge cycle. This model provides an accurate state-of-health (SoH) estimation with a difference of less than 2.22% when compared with the electrochemistry-based electrical (ECBE) SoH calculation. The model parameters derived from a lithium-ion battery can also be applied to other cells in the same pack with less than 2.5% difference from the complex ECBE model, showing the extendibility of the model. The parameters (k1, k2, and k3) calculated in the work can also be used to study the changes in battery internal structure, such as capacity losses at normal conditions, as well as cycling at high temperatures. The time for estimation after each discharge cycle is only 5 s, making it is suitable for on-line in-situ estimation.

Original languageEnglish
Article number3012
JournalApplied Sciences (Switzerland)
Volume9
Issue number15
DOIs
StatePublished - 2019

Bibliographical note

Publisher Copyright:
© 2019 by the authors.

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

  • ECBE model
  • Li-ion batteries
  • Robust and accurate
  • Semi-empirical capacity fading model

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