Carefully monitoring the relevant parameters under all operating conditions is necessary for the safe operation of li-ion batteries (LIB) in a wide variety of different applications. This applies to both the charging and discharging cycles. The manufacturers define tight parameter limits in this regard, and it is important to stay within these limits in order to guarantee the functional safety of the overall system. As a result, battery management must be based on these parameters accordingly.
Gain In-Depth Knowledge of Battery Management from Rutronik’s Experts
The Rutronik workshops are divided into different sessions, each of which covers a specific aspect of battery management. The focus of the sessions includes thermal battery pack management, cell parameters and the resulting BMS software requirements for monitoring, power distribution in cells connected in parallel, hybrid energy systems composed of LIB and supercapacitors, LIB aging diagnostics and the matching selection of semiconductors, as well as passive and electromechanical components.
“Batteries are found in countless objects we use every day. At the same time, we often do not make the most of their capacity. There is significant potential for optimization here and numerous innovative solutions exist – like the hybrid energy management system or impedance spectroscopy – that can help improve cell monitoring and increase their performance. At these workshops, our experts from Rutronik POWER will demonstrate how to get the most out of technical innovations and existing battery-management options,” explains Andreas Mangler, Head of Strategic Marketing at Rutronik.
The workshops are divided into sessions, each of which covers a specific topic:
• Li-Ion Battery Technology Parameters vs. BMS Software Parameters for Monitoring and Cell Balancing
• Thermal Management of Cylindrical LIB – How Do You Improve the Functional Safety of the Battery
• Power Distribution in Cells Connected in Parallel – Why is Cell Selection/Binning So Important?
• Digital Power Management-Based Hybrid Energy Management Systems with LIB and Super Caps
• Extended Battery Monitoring, Analysis, and Diagnostics Based on Electrochemical Impedance
• Robust and Universal Modeling Algorithms for Battery Analysis in Embedded BMS – Machine Learning
and AI in Embedded MCUs
For a list of workshop locations and to register, please visit