Strange, Calum; dos Reis, Goncalo. (2020). Synthetic IR data for the Attia et al. (2020) battery dataset, [dataset]. University of Edinburgh. School of Mathematics. https://doi.org/10.7488/ds/2957.
Data produced to accompany the paper Strange et al. (2021, Feb): Calum Strange, Shawn Li, Richard Gilchrist and Goncalo dos Reis, 2021 Feb, 'Elbows of Internal Resistance Rise Curves in Li-Ion Cells ' (https://www.mdpi.com/1996-1073/14/4/1206). The data completes the dataset of Attia et. al. (2020) (https://www.nature.com/articles/s41586-020-1994-5) of A123 APR18650M1A cylindrical cells cycled in a constant temperature environment under a variety of fast charging protocols, for which IR measurements were not provided. The predictor model for this data was trained on the dataset of Severson et. al. (2019) (https://www.nature.com/articles/s41560-019-0356-8), which contains data for the same type of battery cells (A123 APR18650M1A cylindrical cells) cycled in the same environment. Both datasets and corresponding descriptions can be found at https://data.matr.io/1/.
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