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Energies
Article . 2023 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Energies
Article . 2023
Data sources: DOAJ
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Virtual Development of Advanced Thermal Management Functions Using Model-in-the-Loop Applications

Authors: Jonas Müller; Nico Besser; Philipp Hermsen; Stefan Pischinger; Jürgen Knauf; Pooya Bagherzade; Johannes Fryjan; +2 Authors

Virtual Development of Advanced Thermal Management Functions Using Model-in-the-Loop Applications

Abstract

Development challenges in the automotive industry are constantly increasing due to the high number of vehicle variants, the growing complexity of powertrains, and future legal requirements. In order to reduce development times while maintaining a high level of product quality and financial feasibility, the application of new model-based methods for virtual powertrain calibration is a particularly suitable approach. In this context, TME and FEV combine advanced thermal management models with electronic control unit (ECU) models for model-in-the-loop applications. This paper presents a development process for ECU and on-board diagnostics (OBD) functions of thermal management systems in hybrid electric vehicles. Thanks to the highly accurate 1D/3D-models, optimal control strategies for electrically actuated components can be developed in early development phases. Virtual sensors for local temperatures are developed for the ECU software to enable a cost-effective use of dedicated control functions. Furthermore, an application for OBD cooling system leakage detection is shown. Finally, the transferability of the methodology to a battery cooling system is demonstrated.

Country
Germany
Related Organizations
Keywords

systems engineering, Technology, T, model-in-the-loop, advanced thermal management models, advanced thermal management models; control unit functions; model-in-the-loop; model predictive controls; hybrid electric vehicles; systems engineering; frontloading, control unit functions, hybrid electric vehicles, 620, model predictive controls, info:eu-repo/classification/ddc/620

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    3
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Top 10%
Average
Average
Green
gold