Path Dependent Battery Degradation Dataset Part 1
Models that predict battery lifetime require knowledge of the causes of degradation and operating conditions that accelerate it. 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, bu...
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| Format: | Dataset |
| Language: | English |
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University of Oxford
2020
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| Summary: | Models that predict battery lifetime require knowledge of the causes of degradation and operating conditions that accelerate it. 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. The data collected while the cells were exposed to the combined profiles as well as the reference performance tests and electrochemical impedence spectroscopy data is included in this dataset. Further information is available in the readme.txt file. |
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