Ageing of lithium-ion batteries results in irreversible reduction in performance. Intrinsic variability between cells, caused by manufacturing differences, occurs at all stages of life and increases with age. Researchers need to know the minimum number of cells they should test to give an accurate representation of population variability, since testing many cells is expensive. In this paper, empirical capacity versus time ageing models were fitted to various degradation datasets assuming that the model parameters could be drawn from a distribution describing a larger population. Using a hierarchical Bayesian approach, we estimated the number of cells required to be tested. Depending on the complexity of the ageing model, models with 1, 2 or 3 parameters respectively required data from at least 9, 11 or 13 cells for a consistent fit. This implies that researchers will need to test at least these numbers of cells at each test point in their experiment to capture manufacturing variability.
翻译:锂离子电池老化导致性能不可逆转地下降; 制造差异造成的细胞间内在变异,发生在生命的所有阶段,随着年龄的增长而增加; 研究人员需要知道他们应测试的细胞最低数量,以便准确反映人口变异性,因为许多细胞的测试费用昂贵; 在本文中,经验能力与时间老化模型被安装在各种降解数据集中,假设模型参数可以从描述较大人口的分布中提取; 采用巴耶斯等级方法,我们估计了需要测试的细胞数量; 取决于老化模型的复杂性, 模型有1个、2个或3个参数,需要至少9个、11个或13个细胞的数据,以保持一致; 这意味着研究人员将需要在每次试验点至少测试这些细胞的数量,以捕捉制造变异性。