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@PHDTHESIS{Mller:1027121,
author = {Müller, Jonas},
othercontributors = {Pischinger, Stefan and Andert, Jakob Lukas},
title = {{P}rädiktives {T}hermomanagement für hochflexible
{Z}ero-{I}mpact {H}ybridfahrzeuge},
school = {Rheinisch-Westfälische Technische Hochschule Aachen},
type = {Dissertation},
address = {Aachen},
publisher = {RWTH Aachen University},
reportid = {RWTH-2026-01229},
pages = {1 Online-Ressource : Illustrationen},
year = {2025},
note = {Veröffentlicht auf dem Publikationsserver der RWTH Aachen
University 2026; Dissertation, Rheinisch-Westfälische
Technische Hochschule Aachen, 2025},
abstract = {The development challenges in the automotive industry are
continuously increasing due to new technologies, regulatory
requirements, societal trends, and changing customer
mobility demands. This results in a high diversity of
vehicle variants and a growing complexity of powertrains. In
order to further reduce development times while maintaining
high product quality and economic efficiency, the
application of model-based methods for holistic powertrain
design represents a promising approach. In this context, it
is essential to identify the interactions of relevant target
metrics under real driving conditions, with particular
consideration given to numerous thermal effects within the
powertrain and the driving environment. First, the developed
design methodology is presented using a top-down approach.
Based on this methodology, powertrain-relevant requirements
for an exemplary target customer are translated into a
specification sheet including dedicated test cases.
Subsequently, the relevance of thermal management for
different powertrain design target metrics is theoretically
derived, and the state of the art of current thermal
management systems and their control strategies are
reviewed. To evaluate the resulting requirements, a full
vehicle model with detailed thermal submodels is developed.
Based on standardized test cases, a baseline design of a
C-segment plug-in hybrid vehicle is carried out. The
influence of different customer profiles on the design
outcome is investigated using varying weighting factors. The
target customer design is analyzed in four real-world
driving scenarios with varying parameters such as ambient
temperature and battery state of charge, focusing on the
thermal impact on the target metrics. Finally, the potential
of thermal management technologies and predictive driving
functions is assessed in selected driving scenarios, taking
into account the identified constraints of the baseline
design.},
cin = {412310},
ddc = {620},
cid = {$I:(DE-82)412310_20140620$},
typ = {PUB:(DE-HGF)11},
doi = {10.18154/RWTH-2026-01229},
url = {https://publications.rwth-aachen.de/record/1027121},
}
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