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University of Hawaii

Electrical Engineering

Perspective on State of Health determination in Lithium ion batteries and HNEI battery activity

Date: 2020-05-27           Add to Google Calendar
Time: 10:00am -11:00am
Location: Online via Zoom (contact EE Office for connection details)
Speaker: Dr. Matthieu Dubarry

Abstract
State of health (SOH) is an essential parameter for the proper function of large battery packs. A wide array of methodologies has been proposed in the literature to track state of health, but they often lack the proper validation needed to be universally adaptable to large deployed systems. This is likely induced by the lack of knowledge bridge between material scientists, who understand batteries, and EE engineers, who understand controls. In this seminar, we will attempt to bridge this gap by providing definitions, concepts and tools to apply necessary material science knowledge to advanced battery management systems (BMS). We will address SOH determination and prediction, as well as BMS implementation and validation using the mechanistic framework developed around electrochemical voltage spectroscopies. Particular focus will be set on the onset and the prediction of the second stage of accelerating capacity loss that is commonly observed in commercial lithium ion batteries.


Bio
Matthieu Dubarry (PhD, Electrochemistry & Solid State Science, University of Nantes), has over 15 years of experience in renewable energy, with an emphasis in the area of lithium ion batteries. Following his PhD on the synthesis and characterization of materials for lithium batteries, Dr. Dubarry joined the Hawaii Natural Energy Institute at the University of Hawaii at Mānoa as a post-doctoral fellow in 2005 to work on the analysis of the usage of a fleet of electric vehicles. He was later appointed a faculty position in 2010 with a focus on battery testing, modeling and simulation. While working for HNEI, Dr. Dubarry pioneered the use of new techniques for the non-destructive analysis of the degradation of Li-ion cells and developed numerous software tools facilitating the prognosis of Li-ion battery degradation both at the single cell and the battery pack level. Current projects include the evaluation of grid scale Li-ion battery energy storage systems; the evaluation of the impact of vehicle-to-grid strategies on electric vehicle battery pack degradation; and the testing of emerging battery technologies for grid-connected and transportation applications.



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