A Statistical Model-Based Cell-to-Cell Variability Management of Li-ion Battery Pack

Abstract

The cell-to-cell variability of batteries is a well-known problem particularly when it comes to the assembly of large battery packs. Different battery cells exhibit substantial variability due to manufacturing tolerances, which should be assessed and managed carefully. Such variability has been approached mostly from the point of view of the chemical and physical phenomena, but these solutions are normally too complicated for the system-level design of electric applications. This paper proposes a combined cell-to-cell variability model of the capacity and internal resistance of a Li-ion battery that accounts for the variability effects in the cell manufacturing process. The proposed model allows to verify some known properties, such as the correlation between the capacity and internal resistance, to be verified qualitatively and the amount of variability and its impact on the design of battery packs to be assessed quantitatively. Using this model, the issue of how to consider the variability when constructing battery packs was also addressed. Modern battery packs normally incorporate some cell balancing circuitry, which is meant to balance cell voltages during charging at the expense of a bypassed (unstored) charge. For discharge, the cell-to-cell variability hides a part of the usable capacity of the battery pack. This paper proposes the use of variability information to assemble battery packs with minimal intracolumn variance of capacity. A weight-based variance minimization method, based on the correlation between cell capacity and weight is proposed to avoid resorting to direct battery capacity measurements, which is time-consuming and requires costly measurement equipment. The simulation result shows that the proposed weight-based approach allows an acceptable management of the cell-to-cell variability without the discharging experiment.