Derived Quantities Uncertainty Propagation in High Precision Battery Testing

Abstract

The successful electrification of the transportation and stationary power markets requires batteries with 10–30 years of lifetime. Validations of such long time scales can take several years and require significant confidence in future life predictions. Battery life predictions across such timescales can be highly sensitive to uncertainty in the collection of primary parameters such as current, voltage and time. A methodology to quantify how these primary parameters propagate into the derived parameters of interest such as capacity and coulombic efficiency is presented. The recent development of high precision battery testing and equipment has met the need for accurate and precise assessment of measurement errors. As an example of the derived quantity uncertainty propagation methodology and approach developed in this paper, a prototype high current, high precision tester is also evaluated. The aim of this paper is to describe a standardized method for the precise quantification of battery derived parameter uncertainty, apply the method to the performance of a prototype high current, high precision tester (HPT) as a case study, and then to model the sensitivity of these precision results across a population of possible test conditions.