Abstract
This paper discusses the use of model-based calibration for Li-ion batteries. The scope is set on the modeling algorithm, in this case the Gaussian Process Regression (GPR) in combination with an external dynamic structure (NARX), and its capability to describe dynamic battery behavior. A data-driven model is generated based on measurement of a Stuttgart Cycle. Model quality is evaluated on an Artemis Cycle. The achieved results show that the GPR can be used in a future model-based battery calibration process for dynamic applications in order to increase calibration efficiency.
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© 2016 Springer Fachmedien Wiesbaden
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Behr, L. et al. (2016). Increased efficiency in the calibration process of automotive Li-ion battery systems. In: Bargende, M., Reuss, HC., Wiedemann, J. (eds) 16. Internationales Stuttgarter Symposium. Proceedings. Springer, Wiesbaden. https://doi.org/10.1007/978-3-658-13255-2_9
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DOI: https://doi.org/10.1007/978-3-658-13255-2_9
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Publisher Name: Springer, Wiesbaden
Print ISBN: 978-3-658-13254-5
Online ISBN: 978-3-658-13255-2
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