Design of experiments for optimizing the calendering process in Li-ion battery manufacturing

Calendering is a key yet complex manufacturing process that has varied effects on the Li-ion battery cell performance. Finding optimal compaction can require many experiments if using traditional one-factor-at-a-time method, which would be both and resource intensive. Design of Experiments (DoE) coupled with modeling via multiple linear regression (MLR) are used in this study to better understand electrode calendering. The factors studied report rolling temperature, post-calendered porosity, mass loading NMC622 their effect electrochemical exact combinations these will create an information-rich data set prepared DoE. MLR then extract information form understanding how each factor (individually combination other ones) affect performance cells. Via approach, physical statistical significance quantified. Furthermore, models determine result Overall, highlights use DoE highlight most important regions design space conduct while model system (calendering).