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Comparative evaluation of powertrain concepts through an eco-impact optimization framework with real driving data

Esser, Arved ; Eichenlaub, Tobias ; Schleiffer, Jean-Eric ; Jardin, Philippe ; Rinderknecht, Stephan (2024)
Comparative evaluation of powertrain concepts through an eco-impact optimization framework with real driving data.
In: Optimization and Engineering : International Multidisciplinary Journal to Promote Optimization Theory & Applications in Engineering Sciences, 2021, 22 (2)
doi: 10.26083/tuprints-00023896
Article, Secondary publication, Publisher's Version

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Item Type: Article
Type of entry: Secondary publication
Title: Comparative evaluation of powertrain concepts through an eco-impact optimization framework with real driving data
Language: English
Date: 17 December 2024
Place of Publication: Darmstadt
Year of primary publication: June 2021
Place of primary publication: Dordrecht
Publisher: Springer Science
Journal or Publication Title: Optimization and Engineering : International Multidisciplinary Journal to Promote Optimization Theory & Applications in Engineering Sciences
Volume of the journal: 22
Issue Number: 2
DOI: 10.26083/tuprints-00023896
Corresponding Links:
Origin: Secondary publication DeepGreen
Abstract:

The assessment of the ecological impact of different powertrain concepts is of increasing relevance considering the enormous efforts necessary to limit the global warming effect due to the man-made climate change. Within this contribution, we adopt existing methods for the optimization of electric and hybrid electric powertrains using a vehicle simulation environment and derive a method to identify the ecological potential of different powertrain concepts for a set of technological parameters in the reference year 2030. By optimizing the parametrization for each powertrain concept and by adapting the respective operating behaviour specifically to minimize the ecological impact, a reliable and unbiased comparison is enabled. We use our optimization environment with the Real Ecological Impact as objective function to compare different powertrain concepts on driving profiles that are based on real driving data recorded in Germany. Despite the fact that all of the considered driving profiles contain trips of similar length, their respective optimized powertrain concepts are different. Plug-In Hybrid vehicles achieve the greatest potential for long-range capable vehicles and are least sensitive to different driving profiles.

Uncontrolled Keywords: Ecological impact, Powertrain concepts, Powertrain optimization, Driving profiles
Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-238967
Additional Information:

Part of a collection: Math for SDG 7 - Affordable and Clean Energy

Special Issue on “Technical operations research (TOR)” edited by Armin Fügenschuh, Ulf Lorenz and Peter F. Pelz, and Special Issue on “Multiobjective optimization and decision making in engineering sciences” edited by Jussi Hakanen and Richard Allmendinger

Classification DDC: 600 Technology, medicine, applied sciences > 620 Engineering and machine engineering
Divisions: 16 Department of Mechanical Engineering > Institute for Mechatronic Systems in Mechanical Engineering (IMS)
Date Deposited: 17 Dec 2024 12:47
Last Modified: 17 Dec 2024 12:47
SWORD Depositor: Deep Green
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/23896
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