Accepted manuscript.pdf (1.5 MB)
Rate dependency of incremental capacity analysis (dQ/dV) as a diagnostic tool for lithium-ion batteries
Incremental capacity analysis (ICA) is a widely used method of characterising state of health (SOH) in secondary batteries through the identification of peaks that correspond to active material phase transformations. For reliable ICA, cells are cycled under low constant currents to minimise resistance and diffusion effects, making deployment into applications such as electric vehicle charging unfeasible.
In this work, the influence of charge/discharge rate on ICA is quantitively analysed through peak detection algorithms on two lithium-ion cells with different positive electrodes. Based on these results, a new robust method for faster ICA is introduced which corrects peak shift through SOC dependant resistance measurements using current interrupt. The new technique is evaluated through degradation tests on a Li(NiCoAl)O2/graphite cell. Results demonstrate that ICA during a 6-hour (C/6) charge represents an ideal compromise between diagnostic accuracy and realistic application charge times. ICA at C/6 can predict peak location within 0.59% of a 48-hour charge (C/48) using resistance correction, compared to 1.90% without correction. Under ageing, the C/6 charge was able to correctly identify the trend of each peak compared to C/24 charge and maintain peak location to within 2.0%.
At rates higher than C/6, the number of identifiable peaks in the ICA reduce, most noticeably in aged cells. After 200 cycles, only one identifiable peak was seen at 1C charge compared to four at C/6 and five at C/24.
History
School
- Aeronautical, Automotive, Chemical and Materials Engineering
Department
- Aeronautical and Automotive Engineering
Published in
Journal of Energy StorageVolume
29Publisher
Elsevier BVVersion
- AM (Accepted Manuscript)
Rights holder
© Elsevier LtdPublisher statement
This paper was accepted for publication in the journal Journal of Energy Storage and the definitive published version is available at https://doi.org/10.1016/j.est.2020.101329.Acceptance date
2020-02-26Publication date
2020-03-06Copyright date
2020ISSN
2352-152XPublisher version
Language
- en
Depositor
Dr Ashley Fly. Deposit date: 9 March 2020Article number
101329Usage metrics
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