Reconstruction of the incremental capacity trajectories from current-varying profiles for lithium-ion batteries
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
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Detail(s)
Original language | English |
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Article number | 103103 |
Journal / Publication | iScience |
Volume | 24 |
Issue number | 10 |
Online published | 10 Sept 2021 |
Publication status | Published - 22 Oct 2021 |
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DOI | DOI |
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Link to Scopus | https://www.scopus.com/record/display.uri?eid=2-s2.0-85122814666&origin=recordpage |
Permanent Link | https://scholars.cityu.edu.hk/en/publications/publication(1b53a892-878c-4b78-ac90-fa345fe6db2d).html |
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.
Research Area(s)
- OF-HEALTH ESTIMATION, POLYMER BATTERIES, ONLINE STATE, MODEL, PARAMETERS, REGRESSION, IMPEDANCE
Citation Format(s)
Reconstruction of the incremental capacity trajectories from current-varying profiles for lithium-ion batteries. / Tang, Xiaopeng; Wang, Yujie; Liu, Qi et al.
In: iScience, Vol. 24, No. 10, 103103, 22.10.2021.
In: iScience, Vol. 24, No. 10, 103103, 22.10.2021.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
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