IFAC 2026 Workshop On
Modeling, Estimation, Control, and Learning
Register NowThe safety, performance, and longevity of battery energy storage systems depend heavily on advanced Battery Management Systems (BMS). While decades of research have enabled accurate modeling, state-aware monitoring, and reliable decision-making for systems under demanding operating conditions, fundamental challenges still remain when transitioning battery management algorithms from laboratory settings to real-world deployment.
This full-day workshop at IFAC 2026 brings together leading researchers and practitioners from both academia and industry to bridge this gap. We will explore the full spectrum of modern BMS, including physics-based modeling, advanced state estimation, and the practical deployment of control and fault diagnosis methods for complex battery systems.
World-Class and Diverse Insights
Learn from pioneers across different fields—materials science, control engineering, and machine learning—representing premier academic institutions and global industry leaders.
Academia–Industry Panel
Participate in interactive Q&A forums dedicated to addressing the academia-industry gap and real-world deployment challenges.
Community Building
Connect with a diverse community of experts to shape the future of next-generation battery management systems.
Scott Moura
University of California, Berkeley
Juhyun Song
Korea Institute of Energy Technology
Jaewoong Lee
University of California, Berkeley
Jang Wook Choi
Seoul National University
Juhyun Song
Korea Institute of Energy Technology
Shengyu Tao
Chalmers University of Technology
Huazhen Fang
Michigan State University
Hyunjun Jang
Hyundai Motors
Gwanghoon Jun
LG Energy Solution
* Click on a session to view details
| Time | Speaker | Title |
|---|---|---|
| 08:30–09:00 | Prof. Scott Moura University of California, Berkeley |
Registration & Welcome Reception |
| 09:00–09:45 | Prof. Jang Wook Choi Seoul National University |
Prediction and Diagnosis of Commercial Lithium-Ion Batteries Using Electrochemistry Domain Knowledge |
| 09:45–09:50 | Break | |
| 09:50–10:20 | Prof. Juhyun Song Korea Institute of Energy Technology |
Battery Lifetime Management via Human-Centric Contextual Learning: Application to Delayed Full-Charging |
| 10:20–10:40 | IFAC Coffee Break | |
| 10:40–11:10 | Dr. Shengyu Tao Chalmers University of Technology |
Rapid and Sustainable Battery Health Diagnosis for Recycling Pretreatment Using Fast Pulse Test and Random Forest Machine Learning |
| 11:10–12:00 | Panel Talk (Academia) | |
| 12:00–13:30 | Lunch Break | |
| 13:30–14:00 | Prof. Huazhen Fang Michigan State University |
Confluence of Physics and Machine Learning for Lithium-Ion Battery Modeling |
| 14:00–14:30 | Dr. Hyunjun Jang Hyundai Motors |
AI-Based BMS Algorithm Development from Embedded Deployment to Cloud Integration |
| 14:30–15:00 | Dr. Gwanghoon Jun LG Energy Solution |
Advancing Next-Generation BMS and New Business Models via Physics-Based Battery Modeling |
| 15:00–15:30 | Panel Talk (Industry) | |
| 15:30–15:40 | IFAC Coffee Break | |
| 15:40–16:00 | Closing Remarks | |
| 16:00–17:00 | Networking | |
📍 Registration: BEXCO Convention Hall, 1st Floor
📍 Workshop: BEXCO Exhibition Center 1, Room 213