Performance Analysis of Empirical Open-Circuit Voltage Modeling in Lithium Ion Batteries, Part-3: Experimental Results

TL;DR

This paper analyzes experimental data from lithium-ion batteries to quantify uncertainties in open circuit voltage models, revealing how C-Rate affects model accuracy and aiding in improved battery management.

Contribution

It provides empirical analysis of OCV uncertainties based on extensive experiments, establishing the relationship between C-Rate and model accuracy.

Findings

Lower C-Rate results in smaller OCV-SOC errors

Identifies cell-to-cell variation, cycle-rate error, and curve fitting error as key uncertainties

Quantifies the tradeoff between test duration and model uncertainty

Abstract

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.