Battery calendar aging and machine learning

Abstract

Eric J. Dufek, PhD, is the department manager for the Energy Storage and Electric Transportation Department at Idaho National Laboratory. His research interests span from understanding battery material degradation to electric vehicle infrastructure. Recently he has focused on the use of advanced analysis technigues, including machine learning, to significantly reduce the time needed to make life and failure mode predictions and classifications. By applying these advanced techniques, he hopes to reduce the time needed to transition high-energy and fast-charge battery technologies from the benchtop to consumer adoption. Tanvir R. Tanim, PhD, is an R&D engineer and the group lead for the Energy Storage Technology Group in the Energy Storage and Electric Transportation Department at Idaho National Laboratory. His research focuses on enabling next-generation high-energy and power lithium-ion batteries, developing advanced algorithms for reliable life estimation, and expanding and/or verifying advanced diagnostics and prognostics of these high-energy and power batteries for electric vehicle applications. Between 2011 and 2022, he authored or co-authored 38 peer-reviewed scientific articles and patents. Bor-Rong Chen, PhD, is a staff scientist at Idaho National Laboratory (INL) in the Energy Storage and Electric Transportation Department. She earned a PhD in materials science and engineering from Northwestern University in the US. Her research interest is the early identification of degradation mechanisms in Li-ion batteries and the development of advanced materials for high-energy batteries. Sangwook Kim, PhD, is a staff engineer in the Energy Storage and Electric Transportation Department at Idaho National Laboratory (INL). He obtained his MS and PhD from the Department of Mechanical Engineering at North Carolina State University in 2015 and 2019. During his PhD program, he was awarded a 2018 INL Graduate Fellowship. His current research focuses on understanding aging modes and the development of diagnostic/prognostics tools for advanced lithium-ion and lithium metal batteries. Eric J. Dufek, PhD, is the department manager for the Energy Storage and Electric Transportation Department at Idaho National Laboratory. His research interests span from understanding battery material degradation to electric vehicle infrastructure. Recently he has focused on the use of advanced analysis technigues, including machine learning, to significantly reduce the time needed to make life and failure mode predictions and classifications. By applying these advanced techniques, he hopes to reduce the time needed to transition high-energy and fast-charge battery technologies from the benchtop to consumer adoption. Tanvir R. Tanim, PhD, is an R&D engineer and the group lead for the Energy Storage Technology Group in the Energy Storage and Electric Transportation Department at Idaho National Laboratory. His research focuses on enabling next-generation high-energy and power lithium-ion batteries, developing advanced algorithms for reliable life estimation, and expanding and/or verifying advanced diagnostics and prognostics of these high-energy and power batteries for electric vehicle applications. Between 2011 and 2022, he authored or co-authored 38 peer-reviewed scientific articles and patents. Bor-Rong Chen, PhD, is a staff scientist at Idaho National Laboratory (INL) in the Energy Storage and Electric Transportation Department. She earned a PhD in materials science and engineering from Northwestern University in the US. Her research interest is the early identification of degradation mechanisms in Li-ion batteries and the development of advanced materials for high-energy batteries. Sangwook Kim, PhD, is a staff engineer in the Energy Storage and Electric Transportation Department at Idaho National Laboratory (INL). He obtained his MS and PhD from the Department of Mechanical Engineering at North Carolina State University in 2015 and 2019. During his PhD program, he was awarded a 2018 INL Graduate Fellowship. His current research focuses on understanding aging modes and the development of diagnostic/prognostics tools for advanced lithium-ion and lithium metal batteries.