University of Waterloo Electrochemical Society Student Chapter
Applications of Machine Learning in Battery Research
Wed, Jul 22
|Online Webinar
Have you ever wondered how machine learning could be used in a research field such as battery research? Dr. Kristen Severson, post doctoral fellow at IBM, joins us in an online webinar to share her work in this field and answer our burning questions!
Time & Location
Jul 22, 2020, 10:30 a.m. – 11:45 a.m. EDT
Online Webinar
About the event
About the speaker
Dr. Kristen Severson is a post-doctoral researcher at IBM Research in Cambridge, MA. Her interests are broadly in applied machine learning with a current focus on healthcare applications. Prior to joining IBM, Kristen earned her PhD at MIT where she worked on machine learning applied to problems in lithium-ion batteries, production oil wells, and bioinformatics. She also holds a BS from Carnegie Mellon University.
Webinar abstract
Accurately predicting the lifetime of complex, nonlinear systems such as lithium-ion batteries is critical for accelerating technology development. However, diverse aging mechanisms, significant device variability and dynamic operating conditions have remained major challenges. We generate a comprehensive dataset consisting of 124 commercial lithium iron phosphate/graphite cells cycled under fast-charging conditions, with widely varying cycle lives ranging from 150 to 2300 cycles. Using discharge voltage curves from early cycles yet to exhibit capacity degradation, we apply machine-learning tools to both predict and…