Cell-to-cell variability of batteries is a well-known problem especially when it comes to assembling large battery packs. Different battery cells exhibit substantial variability among them due to manufacturing tolerances, which should be carefully assessed and managed. By joint research with Politecnico di Torino, we propose a combined cell-to-cell variability model of the capacity and of the internal resistance of a Li-Ion battery that accounts for variability effects in the cell manufacturing process. The proposed model allows us to qualitatively verify some known properties such as the correlation between capacity and internal resistance, and quantitatively assess the amount of variability and its impact on the design of battery packs.

Using this model, we also address the issue of how to consider variability when building battery packs. Modern battery packs usually incorporate some cell balancing circuitry, which is supposed to balance cell voltages during charging at the expense of bypassed (unstored) charge. For discharging, cell-tocell variability hides part of usable capacity of the battery pack. We propose to use the variability information to assemble battery packs with minimal intra-column variance of capacity. In order to avoid resorting to direct battery capacity measurement, which is time-consuming and requires costly measurement equipments, we propose a weight-based variance minimization method, based on the correlation between cell capacity and weight. The proposed approach is expected to allow us to properly understand the distribution of battery characteristics much faster than the discharging experiment.

Related Papers

[C-13-10] Donghwa Shin, Massimo Poncino, Enrico Macii and Naehyuck Chang, "A Statistical Model of Cell-to-Cell Variation in Li-Ion Batteries for System-Level Design," in Proceedings of IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED), pp. 94-99, 2013.