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Document type:
Konferenzbeitrag 
Contribution type:
Textbeitrag / Aufsatz 
Author(s):
Daniel Jerouschek, Ömer Tan, Ralph Kennel, Ahmet Taskiran 
Title:
Modeling Lithium-Ion Batteries Using Machine Learning Algorithms for Mild-Hybrid Vehicle Applications 
Abstract:
The prediction of voltage levels in an automotive 48V mild hybrid power supply system is safety-relevant while also enabling greater efficiency. The high power-to-energy ratio in these power supply systems makes exact voltage prediction challenging, so that a method is established to model the behavior of the lithium-ion batteries by means of a recurrent neural network. The raw data are consequently pre-processed with over- and undersampling, normalization and sequentialization algorithms. The r...    »
 
Book / Congress title:
Proceedings of SEST2021 - the 4th International Conference on Smart Energy Systems and Technologies (SEST) 
Organization:
University of Vaasa 2021 
Date of congress:
6-8 September 2021 
Publisher:
IEEE 
Date of publication:
27.09.2021 
Year:
2021 
Quarter:
3. Quartal 
Year / month:
2021-09 
Month:
Sep 
Print-ISBN:
978-1-7281-7661-1 
E-ISBN:
978-1-7281-7660-4 
Reviewed:
ja 
Language:
en 
Semester:
SS 21 
TUM Institution:
Lehrstuhl für Elektrische Antriebssysteme und Leistungselektronik