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Development of an Optimization Framework for the Comparative Evaluation of the Ecoimpact of Powertrain Concepts

Eßer, Arved ; Schleiffer, J.-E. ; Eichenlaub, Tobias ; Rinderknecht, Stephan (2020)
Development of an Optimization Framework for the Comparative Evaluation of the Ecoimpact of Powertrain Concepts.
19. Internationaler VDI-Kongress "Dritev - Getriebe in Fahrzeugen".
doi: 10.25534/tuprints-00011299
Conference or Workshop Item, Secondary publication

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Item Type: Conference or Workshop Item
Type of entry: Secondary publication
Title: Development of an Optimization Framework for the Comparative Evaluation of the Ecoimpact of Powertrain Concepts
Language: English
Date: 2020
Place of Publication: Bonn, 10.-11. Juli 2019
Year of primary publication: 2019
Series: VDI-Berichte
Series Volume: 2354
Event Title: 19. Internationaler VDI-Kongress "Dritev - Getriebe in Fahrzeugen"
DOI: 10.25534/tuprints-00011299
Origin: Secondary publication
Abstract:

The state of the art in the evaluation of the ecological impact of various powertrain concepts is based on the evaluation of characteristics of existing vehicles on the market. However, these vehicles were developed with different objectives and are operated with various usage profiles. The potential of the powertrain concepts, if they were optimally designed for a given parameter set of a scenario to be investigated, remains unclear. But the knowledge of these optimal parametrizations of the powertrain concepts is necessary to enable an unbiased comparison of the technologies, especially if future scenarios are considered in which significant deviations from current parameter sets are possible. This work is based on results of the publicly funded FahrKLang project, in which an optimization framework for the comparative assessment of the "Real Ecological Impact" (REI) of various powertrain concepts has been developed. For each investigated scenario, optimal powertrain parametrizations of the various concepts to minimize the REI and a customized operational strategy are identified, thereby creating an equal evaluation basis. Representative driving cycles enable an efficient evaluation of the concepts based on real fleet driving data within the optimization environment.

URN: urn:nbn:de:tuda-tuprints-112996
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: 30 Jan 2020 14:50
Last Modified: 21 Jun 2023 14:03
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/11299
PPN: 46074934X
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