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 PublicationsJournal Article (refereed)peer-review

29 Citations (Scopus)

Abstract

The reliable assessment of battery degradation is fundamental for safe and efficient battery utilization. As an important in situ health diagnostic method, the incremental 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 reconstructed 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
Early online date10 Sept 2021
DOIs
Publication statusPublished - 22 Oct 2021
Externally publishedYes

Bibliographical note

Funding Information:
The first author would like to thank the Guangzhou HKUST Fok Ying Tung Research Institute for the continuing support during the Hong Kong's unrest and 2019-nCoV's outbreak. This work is supported partly by the National Natural Science Foundation of China (Grant No. 61803359), the University Synergy Innovation Program of Anhui Province (Grant No. GXXT-2019-002), Guangdong Scientific and Technological Project (Grant No. 2017B010120002), Guangzhou Scientific and Technological Project (Grant No. 202002030323), Hong Kong Research Grant Council (Grant No. 16207717 and 16208520), and the Shenzhen Science and Technology Innovation Commission under the grant Shenzhen-Hong Kong Innovation Circle Category D Project: SGDX 2019081623240948. X.T. and F.G. conceived the study and carried out the experiments. X.T. and Y.W. developed the solution, analyzed the experimental results, and drafted the manuscript. X.T. also implemented the programming. Q.L. and F.G. discussed the technical details, analyzed the data, revised, and polished the manuscript. All authors commented on the manuscript. The authors declare no competing interests.

Publisher Copyright:
© 2021 The Author(s)

Keywords

  • Energy Management
  • Energy storage
  • Energy Systems

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