Symposium on Physics and Machine Learning for Batteries

October 23, 2023 in Aachen, Germany

 

Welcome to the Symposium on Physics and Machine Learning for Batteries! This groundbreaking event brings together top researchers in the field of batteries, uniting the realms of physics and machine learning to explore battery-related research at every level, from materials to systems. Our symposium is dedicated to fostering collaboration and knowledge exchange among experts and enthusiasts in the battery community. What sets our event apart is the emphasis on the convergence of physics and machine learning approaches in advancing battery technology.

Through a carefully curated selection of outstanding speakers, we will delve into the latest developments and applications in both physics-based and machine learning-driven battery research. From understanding the atomistic behaviour of materials to studying the continuum modelling of batteries and from the integration of control systems to exploring novel machine learning algorithms, our symposium aims to facilitate open discussions and spark innovative ideas. Attendees can expect broad and inspiring presentations, covering diverse topics that span the entire battery ecosystem.

We invite you to join us in this exciting journey at the Symposium on Physics and Machine Learning for Batteries, where you will have the opportunity to connect with leading researchers, share your insights, and contribute to cutting-edge advancements in battery technology. Together, we will explore the convergence of physics and machine learning to unlock the full potential of batteries, paving the way for a sustainable and energy-efficient future.

 

Speakers

 

Catalyzing research from the benchtop to the gigafactory

Dr. Helge Sören Stein, Associate Professor, Technical University of Munich (TUM)

Dr. Helge Stein holds an MSc. in Physics from the University of Göttingen and obtained his doctoral degree (Dr.-Ing.) from Ruhr University Bochum in 2017. Having worked as a researcher at Caltech until 2020, Dr. Stein was subsequently appointed as a Tenure Track Professor at Karlsruhe Institute of Technology (KIT) and, in 2023, achieved the position of Associate Professor at the esteemed Technical University of Munich (TUM).

 
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  Birger Horstman

Physics-based models for SEI on graphite and silicon electrodes: How can machine learning help?

Dr. Birger Horstmann, Professor and Group Leader, German Aerospace Center (DLR)

Professor Birger Horstmann is Group Leader at the German Aerospace Center (DLR) in the Helmholtz Institute Ulm and is Professor of Materials Simulation. He studied Physics and Mathematics at the University of Jena and the University of Cambridge. After completing his PhD on theoretical quantum physics at the Max-Planck-Institute for Quantum Optics near Munich, Dr. Horstmann moved to the field of continuum modelling of batteries. His current research focuses on mesoscale models for electrochemical interfaces and interphases. This includes the theory of electrochemical double layers, nucleation and growth of reaction products, and the formation of interphases, e.g. SEI. Furthermore, he evaluates these mesoscale theories in macroscopic models of lithium and beyond lithium batteries.

 
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Multi-scale battery modelling and the pathway to digital twins

Dr. Billy Wu, Reader (Associate Professor), Imperial College London

Dr. Billy Wu is a Reader (Associate Professor) and Director of Research in the Dyson School of Design Engineering at Imperial College London. He co-leads the Electrochemical Science and Engineering group, which works at the interface between fundamental science and engineering applications of electrochemical devices, including batteries, supercapacitors and fuel cells. Cross-cutting activities include energy materials, understanding degradation, modelling, diagnostics, thermal management and techno-economics.

 
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  Maitane-Berecibar

The batteries is the future, key research actions

Dr. Maitane Berecibar, Professor, Vrije Universiteit Brussel (VUB)

Prof Dr Ir Maitane Berecibar obtained her PhD in Engineering of Sciences at the VUB in August 2017 titled “Development of an Accurate State of Health Estimation Technique for Lithium-Ion Batteries”. Since 2019, prof Berecibar is the Head of the Battery Innovation Center in the MOBI research group at VUB. She is now in charge of R&D innovation and strategy on the field of batteries considering; emerging battery technologies , battery manufacturing, self-healing properties, sensor integration, modeling activities, smart SoX estimations, cooling system development, management strategies and second life. As the team leader she focuses on developing new consortium, management of promising innovative projects and supervising her group which counts with 20 people. Prof Berecibar is an official member of the IEC standardization body, and she is scientific reviewer on several Conferences and Journal Publications. She has participated as jury member in several PhD thesis, both at VUB, and in other international universities. She has recently won the Francqui Start Up Research Award at Belgium level.

 
  Sebastian Ohneseit Copyright: © FOTO by SOUSA

Experimental study of thermal and mechanical safety by thermal runaway testing of cylindrical LIB with different cathode materials

Dipl.-Ing. Sebastian Ohneseit, Karlsruhe Institute of Technology (KIT)

Dipl.-Ing. Sebastian Ohneseit earned a German-French double degree in Mechanical and Energy Engineering from TU Kaiserslautern and INSA Rouen. Since 2020 he is working as a research associate in the Group Batteries – Calorimetry and Safety at the Institute of Applied Materials (IAM-AWP) of Karlsruhe Institute of Technology (KIT), under the supervision of Dr. Carlos Ziebert and Prof. Dr. Hans J. Seifert. His research covers experimental thermal runaway analysis of LIB, mainly by Accelerating Rate Calorimetry. In addition he is investigating cell aging behavior and possibilities to control, stop and extinguish batteries undergoing thermal runaway.

 
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  Copyright: © DAVID AUSSERHOFER

Machine learning for efficient and reliable battery use in mobility and energy supply

Dr. Weihan Li, Junior Research Group Leader, RWTH Aachen University

Dr. Weihan Li heads the "Artificial Intelligence for Batteries" research group at RWTH Aachen University since 2022. He earned a Ph.D. in electrical engineering with highest honors from RWTH Aachen in 2021, following an M.S. in automotive engineering from RWTH Aachen in 2017, and a B.S. in automotive engineering from Tongji University in 2014. He conducted research at Imperial College London, University of Oxford, and MIT as a visiting researcher and has held engineering roles at Volkswagen AG and Porsche Engineering GmbH. Weihan Li's research group focuses on battery modeling, testing, and control from material to system levels, utilizing physics-based and machine learning approaches.

 
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Program

09:00-09:30 Registration and refreshments

09:30-09:45 Welcome - Prof. Dirk Uwe Sauer and Dr. Weihan Li,
CARL, RWTH Aachen University

09:45-10:30 Weihan Li, CARL, RWTH Aachen University:
Machine learning for efficient and reliable battery use in
mobility and energy supply


10:30-11:15 Birger Horstmann, German Aerospace Center:
Physics-based models for SEI on graphite and silicon
electrodes: How can machine learning help?


11:15-11:30 Break

11:30-12:15 Maitane Berecibar, Vrije Universiteit Brussel:
The batteries is the future, key research actions

12:15-13:15 Lunch & Posters

13:15-14:00 Billy Wu, Imperial College London:
Multi-scale battery modelling and the pathway to digital
twins


14:00-14:45 Sebastian Ohneseit, Karlsruhe Institute of Technology:
Experimental study of thermal and mechanical safety by
thermal runaway testing of cylindrical LIB with different
cathode materials


14:45-15:00 Break

15:00-15:45 Helge Stein, Technical University of Munich:
Catalyzing research from the benchtop to the gigafactory

15:45-16:00 Break

16:00-18:00 CARL Tour

Program available as PDF download at the bottom of the page

 

Venue and Accommodation

The Symposium on Physics and Machine Learning for Batteries will be held at the Center for Ageing, Reliability and Lifetime Prediction of Electrochemical and Power Electronic Systems (CARL), RWTH Aachen University, Campus-Boulevard 89, 52074 Aachen, Germany.

Map


Registration

Registration is closed.

 

Symposium Organizers

Dr. Weihan Li
Dr. Dirk Uwe Sauer

Contact

Please contact for general queries about the conference.

 

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