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Reconstruction of the incremental capacity trajectories from current-varying profiles for lithium-ion batteries

  • Xiaopeng Tang
  • , Yujie Wang*
  • , Qi Liu
  • , Furong Gao*
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

88 Downloads (CityUHK Scholars)

Abstract

The reliable assessment of battery degradation is fundamental for safe and effi-cient battery utilization. As an important in situ health diagnostic method, the in-cremental capacity (IC) analysis relies highly on the low-noise constant-current profiles, which violates the real-life scenarios. Here, a model-free fitting process is reported, for the first time, to reconstruct the IC trajectories from noisy or even current-varying profiles. Based on the results from overall 22 batteries with three case studies, the errors of the peak positions in the reconstructed IC trajectories can be bounded within only 0.25%. With health indicators extracted from the re-constructed IC trajectories, the state of health can be readily determined from simple linear mappings, with estimation error lower than 1% only. By enabling the IC-based methods under complex load profiles, enhanced health assessment could be implemented to improve the reliability of the power systems and further promoting a more sustainable society.
Original languageEnglish
Article number103103
JournaliScience
Volume24
Issue number10
Online published10 Sept 2021
DOIs
Publication statusPublished - 22 Oct 2021

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

Research Keywords

  • OF-HEALTH ESTIMATION
  • POLYMER BATTERIES
  • ONLINE STATE
  • MODEL
  • PARAMETERS
  • REGRESSION
  • IMPEDANCE

Publisher's Copyright Statement

  • This full text is made available under CC-BY-NC-ND 4.0. https://creativecommons.org/licenses/by-nc-nd/4.0/

RGC Funding Information

  • RGC-funded

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