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2019 | OriginalPaper | Chapter

Automated & cloud-based load profile-generation and evaluation of lithium ion batteries

Authors : Alexander Kohs, Thomas Freudenmann, Fabian Back, Mohannad El-Haji, Tobias Schilling, Praveen Kumar Kuppusamy

Published in: 19. Internationales Stuttgarter Symposium

Publisher: Springer Fachmedien Wiesbaden

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Abstract

Today lithium ion batteries (LIB) are the state-of-the-art technology for traction batteries in electric vehicles due to their high energy capacity and output as well as power density. However, the determination of the aging and performance of the LIB remains a challenge, since these essential parameters are highly dependent on the vehicle, user behaviour and environmental conditions. Therefore, traction batteries have the necessity to be constantly monitored by the vehicle electronics. In addition, new methods are needed for the efficient evaluation and diagnosis of the LIB, which are used during development, production and subsequent operation.In this paper, a fully automated, cloud-based process is introduced, which includes the measurement of the LIB during operation, the generation of load profiles at cell level and transfer to battery test benches. To determine the load profile, the combination of the driving profile of the vehicle (for example GPS data) with the load acting on the installed LIB cells takes place.With the help of a central cloud-based IT platform, data loggers, battery test stands and Key Performance Indicators (KPIs) for the aging process of LIB are networked to automatically integrate the generated load profiles into laboratory test series, thus enabling efficient and customer - oriented development.Thus, all battery types in the lab can be loaded with the critical load profile of the specific vehicle and user behaviour, the best technology for the intended use can be determined and vehicles with optimized range, charging time and lifetime can be developed.

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Metadata
Title
Automated & cloud-based load profile-generation and evaluation of lithium ion batteries
Authors
Alexander Kohs
Thomas Freudenmann
Fabian Back
Mohannad El-Haji
Tobias Schilling
Praveen Kumar Kuppusamy
Copyright Year
2019
DOI
https://doi.org/10.1007/978-3-658-25939-6_107