AI Fast Track to Battery Fast Charge

Arghya Bhowmik, Tejs Vegge*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review


In the February 20th issue of Nature, William Chueh and colleagues present a closed-loop optimization strategy for the fast charging of battery cells using early cycle life predictions obtained from machine learning models and Bayesian optimization.1 The developed strategy uses limited testing to obtain substantial improvements in the cycle life of commercial battery cells and aptly demonstrates how machine learning and AI can fast track the performance optimization of battery materials and cells.

Original languageEnglish
Issue number4
Pages (from-to)717-719
Publication statusPublished - 2020

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