Eßer, Arved ; Eichenlaub, Tobias ; Rinderknecht, Stephan (2020)
Real-Driving-Based Comparison of the Eco-Impact of Powertrain Concepts using a Data-Driven Optimization Environment.
20. Internationaler VDI-Kongress "Dritev - Getriebe in Fahrzeugen". Online (24.06.2020 - 25.06.2020)
Konferenzveröffentlichung, Bibliographie
Dies ist die neueste Version dieses Eintrags.
Kurzbeschreibung (Abstract)
In order to limit the effects of man-made climate change, the assessment of the ecological impact of different powertrain concepts is of increasing relevance and intensely studied. In this contribution we present a data-driven optimization environment that enables to identify the ecological potential of different concepts for different scenarios. The parametrization of each powertrain concept is dedicatedly optimized to minimize the ecological impact, which allows for an unbiased and reliable comparison on an uniform evaluation basis. To exploit the potential of each single powertrain parametrization, the operating strategy of the powertrain is adapted. Naturalistic driving profiles, including the speed, acceleration and road-slope information are depicted by multidimensional and representative driving cycles, allowing for an efficient search of the real-driving-optimal powertrain parametrizations within the optimization. In this study, we investigate long-range capable vehicles for a scenario in the reference year 2030 in Germany. Conventional vehicles, battery electric vehicles, fuel cell electric vehicles and plug-in hybrid electric vehicles are examined. Finally, the results are compared to an evaluation of the CO2 emissions according to the Worldwide harmonized Light vehicles Test Procedure (WLTP).
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2020 |
| Autor(en): | Eßer, Arved ; Eichenlaub, Tobias ; Rinderknecht, Stephan |
| Art des Eintrags: | Bibliographie |
| Titel: | Real-Driving-Based Comparison of the Eco-Impact of Powertrain Concepts using a Data-Driven Optimization Environment |
| Sprache: | Englisch |
| Publikationsjahr: | 2020 |
| Ort: | Onlinekonferenz |
| Reihe: | VDI-Berichte |
| Band einer Reihe: | 2373 |
| Veranstaltungstitel: | 20. Internationaler VDI-Kongress "Dritev - Getriebe in Fahrzeugen" |
| Veranstaltungsort: | Online |
| Veranstaltungsdatum: | 24.06.2020 - 25.06.2020 |
| Zugehörige Links: | |
| Kurzbeschreibung (Abstract): | In order to limit the effects of man-made climate change, the assessment of the ecological impact of different powertrain concepts is of increasing relevance and intensely studied. In this contribution we present a data-driven optimization environment that enables to identify the ecological potential of different concepts for different scenarios. The parametrization of each powertrain concept is dedicatedly optimized to minimize the ecological impact, which allows for an unbiased and reliable comparison on an uniform evaluation basis. To exploit the potential of each single powertrain parametrization, the operating strategy of the powertrain is adapted. Naturalistic driving profiles, including the speed, acceleration and road-slope information are depicted by multidimensional and representative driving cycles, allowing for an efficient search of the real-driving-optimal powertrain parametrizations within the optimization. In this study, we investigate long-range capable vehicles for a scenario in the reference year 2030 in Germany. Conventional vehicles, battery electric vehicles, fuel cell electric vehicles and plug-in hybrid electric vehicles are examined. Finally, the results are compared to an evaluation of the CO2 emissions according to the Worldwide harmonized Light vehicles Test Procedure (WLTP). |
| Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften und Maschinenbau |
| Fachbereich(e)/-gebiet(e): | 16 Fachbereich Maschinenbau 16 Fachbereich Maschinenbau > Institut für Mechatronische Systeme im Maschinenbau (IMS) |
| Hinterlegungsdatum: | 28 Jun 2024 08:20 |
| Letzte Änderung: | 28 Jun 2024 08:20 |
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| Suche nach Titel in: | TUfind oder in Google |
Verfügbare Versionen dieses Eintrags
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Real-Driving-Based Comparison of the Eco-Impact of Powertrain Concepts using a Data-Driven Optimization Environment. (deposited 16 Jul 2020 13:10)
- Real-Driving-Based Comparison of the Eco-Impact of Powertrain Concepts using a Data-Driven Optimization Environment. (deposited 28 Jun 2024 08:20) [Gegenwärtig angezeigt]
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