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Path Dependent Battery Degradation Dataset Part 2

Alternative title:
Continuation of Path Dependent Battery Degradation Dataset Part 1, T. Raj, D. A. Howey
Documentation:
Batteries experience two aging modes: calendar aging at rest and cyclic aging during the passage of current. Existing empirical aging models treat these as independent, but degradation may be sensitive to their order and periodicity – a phenomenon that has been called ‘path dependence’. This long-term dataset was collected to study the influence of path dependence in commercially available lithium-ion 18650 cells with nickel cobalt aluminium oxide (NCA) positive electrodes and graphite negative electrodes. Four groups of 3 cells each were subjected to combined load profiles comprising fixed periods of calendar and cyclic aging applied in various orders. Cells in groups 1 and 2 were exposed to one day of cycling followed by five days of calendar aging at C/2 and C/4 respectively. Cells in groups 3 and 4 were exposed to two days of cycling followed by ten days of calendar aging at C/2 and C/4 respectively. All cycling in the combined load profiles was conducted under constant current (CC) conditions and calendar aging was conducted at 90% state of charge (SoC). Cells in group 5 were exposed to continuous CC cycling at C/2 while group 6 consists of a single cell calendar aged at 90% SoC. This dataset is a continuation of the 'Path Dependent Battery Degradation Dataset Part 1, DOI: 10.5287/bodleian:v0ervBv6p ' dataset. Path Dependent Battery Degradation Dataset Part 1 includes data collected over 1.5 years from the beginning of life to the middle of life. Path Dependent Battery Degradation Dataset Part 2 covers the remaining 1.5 years of data from the middle of life to end of life. The data collected while the cells were exposed to the combined profiles as well as the reference performance tests and electrochemical impedance spectroscopy data is included in this dataset. Further information is available in the readme.txt file.

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Data collector, Creator

Contributors

Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Contributor


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Funder identifier:
http://dx.doi.org/10.13039/501100000266
Grant:
D4T00061 DF00.01


Publisher:
University of Oxford
Publication date:
2021
Digital storage location:
https://howey.eng.ox.ac.uk/data-and-code/
DOI:
Temporal coverage:
2017 - 2020


Language:
English
Keywords:
Subjects:
Deposit date:
2021-02-25

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