Are you curious about how battery management systems (BMS) function and their critical role in ensuring the safety and efficiency of energy storage solutions? Would you like to learn about the advanced methods used to estimate battery states, manage aging, and optimize performance? Then this course is perfect for you, even if you don’t have a very related background.
General information
This Tracks course will provide you the basic knowledge about battery management systems (BMS) and provides students with the opportunity to develop expertise in this important technology. Through lectures and hands-on projects, students will gain a detailed understanding of how BMS operates, its role in energy storage, and the latest industry practices in managing battery performance. You will explore different modeling techniques, including equivalent circuit models, electrochemical models, and perform state and model parameter estimation tasks. You will also analyze thermal control strategies and learn how to diagnose and predict battery aging. Throughout the course, you will work closely with both physics-based and data-driven models, applying these insights to ensure battery systems are safe, efficient, and long-lasting.
An important aspect of this course is its strong focus on practical application. You will simulate and manage battery cell behavior under different conditions. By the end of the course, you will have hands-on experience with modern tools and techniques for optimizing battery performance and longevity, similar to what is used in leading battery research labs and industries.
Prerequisites
All master’s students, PhD candidates, and Chalmers alumni with an interest in battery management systems, modeling and control, state estimation, fast charging, machine learning applications in battery research, and battery aging studies are welcome.
How to apply:
Application is open from Nov 12 – Nov 26 at universityadmissions.se/antagning.se.Search for TRA445.
Alumni, PhD students and professionals apply by email to changfu.zou@chalmers.se
Details
Teachers: Torsten Wik, Changfu Zou, Yicun Huang, Xiaolei Bian, industrial guest lecturers
Course dates: Jan – Mar 2024 (SP3)
Credits: 7.5
Level: A
Course code: TRA445
Application deadline: Nov 12 – Nov 26