Predicting the impact of formation protocols on battery lifetime immediately after manufacturing

TL;DR

This paper proposes using low-state-of-charge cell resistance as a quick, inexpensive diagnostic to predict long-term battery lifetime, enabling faster formation protocols without sacrificing battery quality.

Contribution

It introduces a novel, rapid diagnostic signal based on cell resistance at low states of charge for assessing formation protocols' impact on battery lifetime.

Findings

Resistance correlates with cycle life.

Signal improves lifetime prediction accuracy.

Measurement is quick and requires no special equipment.

Abstract

Increasing the speed of battery formation can significantly lower lithium-ion battery manufacturing costs. However, adopting faster formation protocols in practical manufacturing settings is challenging due to a lack of inexpensive, rapid diagnostic signals that can inform possible impacts to long-term battery lifetime. This work identifies the cell resistance measured at low states of charge as an early-life diagnostic feature for screening new formation protocols. We show that this signal correlates to cycle life and improves the accuracy of data-driven battery lifetime prediction models. The signal is obtainable at the end of the manufacturing line, takes seconds to acquire, and does not require specialized test equipment. We explore a physical connection between this resistance signal and the quantity of lithium consumed during formation, suggesting that the signal may be broadly applicable for evaluating any manufacturing process change that could impact the total lithium consumed during formation.