Predicting the Impact of Formation Protocols on Battery Lifetime Immediately After Manufacturing

Abstract

Increasing the speed of battery formation can significantly lower lithium ion battery manufacturing costs. However, adopting faster formation protocols in real manufacturing settings is challenging due to a lack of inexpensive, rapid diagnostic signals that can inform possible impacts to long term battery lifetime. In this work, we identify 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 add any additional capital cost. We explore a physical connection between this resistance signal and the amount of lithium consumed during formation, which suggests that the technique may be broadly applicable for evaluating any battery manufacturing process or design change that could impact the total lithium consumed during formation. This work demonstrates that carefully engineered, simple features can provide useful diagnostics and prognostics for battery degradation at the beginning of life.