Estimation of Li-ion degradation test sample sizes required to understand cell-to-cell variability

TL;DR

This paper uses hierarchical Bayesian models to determine the minimum number of lithium-ion cells needed to accurately capture manufacturing variability in aging tests, aiding efficient experimental design.

Contribution

It introduces a hierarchical Bayesian approach to estimate the required sample size for lithium-ion battery aging studies, considering model complexity and variability.

Findings

At least 9, 11, or 13 cells are needed depending on model complexity.

The method provides a statistical basis for sample size determination in battery aging tests.

Researchers can optimize testing efforts based on these estimates.

Abstract

Ageing of lithium-ion batteries results in irreversible reduction in performance. Intrinsic variability between cells, caused by manufacturing differences, occurs throughout 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 for commercially available cells assuming the model parameters could be drawn from a larger population distribution. Using a hierarchical Bayesian approach, we estimated the number of cells required to be tested. Depending on the complexity, ageing models with 1, 2 or 3 parameters respectively required data from at least 9, 11 or 13 cells for a consistent fit. This implies researchers will need to test at least these numbers of cells at each test point in their experiment to capture manufacturing variability.