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TY  - THES
AU  - Jöst, Dominik
TI  - Modellbasierte Bewertung von Algorithmen zur Zustandsbestimmung von Batterien: Analyse von Betriebs-, Zell- und Messtechnik-Parametern
VL  - 195
PB  - Rheinisch-Westfälische Technische Hochschule Aachen
VL  - Dissertation
CY  - Aachen
M1  - RWTH-2025-10245
T2  - Aachener Beiträge des ISEA
SP  - 1 Online-Ressource : Illustrationen
PY  - 2025
N1  - Veröffentlicht auf dem Publikationsserver der RWTH Aachen University 2026
N1  - Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen, 2025
AB  - The energy transition and the shift towards sustainable mobility require advanced battery technologies, such as lithium-ion battery systems. In every battery storage system, the Battery Management System (BMS) plays a central role by undertaking critical monitoring tasks, thereby being essential for the safety, efficiency, and longevity of the battery system. Although research is increasingly focusing on complex measurement techniques and algorithms for precise state estimation, simple methods that do not achieve the accuracy and robustness of advanced approaches still dominate in practice. This is often due to the high hardware requirements that increase system costs, as well as challenges in validating these algorithms under variable operating conditions. This work aims to address challenges in the development and validation of BMS algorithms that have not been systematically discussed. The focus is on developing and applying a model-based concept that allows comprehensive and efficient analysis of BMS algorithms by simulating battery systems, BMS electronics, and BMS algorithms in a virtual environment. The first part of the dissertation introduces the fundamental aspects of lithium-ion technology and the BMS, including relevant hardware and software components and validation methods. The second part presents the developed modelling environment and its application in the development and validation of battery diagnostics. A detailed reference model of the battery system, combined with an application and BMS emulation, enables the realistic investigation of diagnostic algorithms. Through comprehensive discussion of the battery states to be determined, relevant aspects of validation are identified. Finally, exemplary case studies demonstrate the practical relevance and application of the developed methodology, opening new perspectives for the optimization of battery systems and supporting the energy transition.
LB  - PUB:(DE-HGF)11 ; PUB:(DE-HGF)3
DO  - DOI:10.18154/RWTH-2025-10245
UR  - https://publications.rwth-aachen.de/record/1022768
ER  -