  This paper is the third part of a series of papers about empirical approaches
to open circuit voltage (OCV) modeling of lithium-ion batteries. The first part
of the series proposed models to quantify various sources of uncertainties in
the OCV models; and, the second part of the series presented systematic data
collection approaches to compute the uncertainties in the OCV-SOC models. This
paper uses data collected from 28 OCV characterization experiments, performed
according to the data collection plan presented, to compute and analyze the
following three different OCV uncertainty metrics: cell-to-cell variations,
cycle-rate error, and curve fitting error. From the computed metrics, it was
observed that a lower C-Rate showed smaller errors in the OCV-SOC model and
vice versa. The results reported in this paper establish a relationship between
the C-Rate and the uncertainty of the OCV-SOC model. This research can be thus
useful to battery researchers for quantifying the tradeoff between the time
taken to complete the OCV characterization test and the corresponding
uncertainty in the OCV-SOC modeling. Further, quantified uncertainty model
parameters can be used to accurately characterize the uncertainty in various
battery management functionalities, such as state of charge and state of health
estimation.
