MPEL Seminar: Professor Matthias Preindl, Columbia University

Wednesday, December 7, 2022
1:00 p.m.
AV Williams Room 2460 or Via Zoom
Darcy Long
301 405 3114
dlong123@umd.edu

"Towards High Performance Battery Pack Management using Pulse Injection Aided Machine Learning"

Zoom Link: https://umd.zoom.us/j/93647423223?pwd=c2ZyOHEydXVtcHcvazkrSnhIZmhZdz09

Abstract: Lithium-ion battery (LIB) degradation is often characterized at three distinct levels: mechanisms, modes, and metrics. Recent trends in diagnostics and prognostics have been heavily influenced by machine learning (ML). ML can be leveraged to gain a unique multi-level perspective on characterizing LIB degradation and it can improve accuracy especially when combined with perturbation techniques. This pulse injection aided machine learning technique (PIAML) matches or exceeds existing techniques that lay the foundations for this framework. It is compatible with typical battery pack designs and does not require dedicated sensors or electronics. This framework can inform optimal management of lithium-ion systems, thus extending lifetimes and reducing costs.

Bio: Matthias Preindl received the B.Sc. degree from the University of Padua (summa cum laude, 2008), the M.Sc. degree from ETH Zurich (2010), and the Ph.D. degree from the University of Padua (2014), in electrical engineering. He is an Associate Professor at Columbia University, USA. Prior to joining Columbia in 2016, he was an R&D Engineer of Power Electronics and Drives at Leitwind AG (2010-2012) and a Post-Doctoral Research Associate at McMaster University, Canada (2014-2015). Dr. Preindl serves as Area Editor of IEEE Transactions on Vehicular Technology and was the general chair of 2022 IEEE/AIAA ITEC+EATS. He is a Fellow of IET, Senior Member of IEEE, recipient of the NSF CAREER Award (2017), IEEE Transactions on Industrial Electronics best paper award (2019), co-recipient of Fast Company's World Changing Ideas Awards honorable mention (2022), and MIT A+B best paper award (2022). His research interests include the design and control of motor drives, power electronics, and batteries for transportation electrification and renewable energy.

 

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