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Rate dependency of incremental capacity analysis (dQ/dV) as a diagnostic tool for lithium-ion batteries
journal contributionposted on 09.03.2020 by Ashley Fly, Rui Chen
Any type of content formally published in an academic journal, usually following a peer-review process.
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.
- Aeronautical, Automotive, Chemical and Materials Engineering
- Aeronautical and Automotive Engineering