Authors:
Christoph Schrade
1
;
Theo Zschörnig
2
;
Leonard Kropkowski
3
and
Bogdan Franczyk
1
;
2
Affiliations:
1
Information Systems Institute, Leipzig University, Grimmaische Str. 12, 04109 Leipzig, Germany
;
2
Institute for Applied Informatics (InfAI), Goerdelerring 9, 04109 Leipzig, Germany
;
3
Fraunhofer-Institut für Nachrichtentechnik, Heinrich-Hertz-Institut HHI, Einsteinufer 37, 10587 Berlin, Germany
Keyword(s):
Internal Short Circuit, Energy Storage System, Battery Electric Vehicle, Battery Energy Storage System, Data Driven Early Detection.
Abstract:
Due to national and international laws and regulations, the number of energy storage systems has risen sharply in recent years. While battery systems in operation can often be monitored by installed battery management systems to ensure safe operation, there are still no standardized monitoring methods for batteries during transport or storage. Consequently, this article proposes a solution for monitoring such batteries in the typical logistic processes of storage and transport. Particular attention is paid to a resource-efficient implementation of a data-driven algorithm that is adopted from existing literature and enables the early detection of internal short circuits, which are the main cause of thermal runaways of battery storage systems. As the transmission frequency of an external monitoring device is a particularly resource-critical variable, the extent to which different data frequencies influence the detection performance is also investigated.