Comparative evaluation of powertrain concepts through an eco-impact optimization framework with real driving data
| Autor: | Philippe Jardin, Tobias Eichenlaub, Stephan Rinderknecht, J.-E. Schleiffer, Arved Esser |
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| Rok vydání: | 2020 |
| Předmět: |
Control and Optimization
Computer science Powertrain Mechanical Engineering 0211 other engineering and technologies Aerospace Engineering 020302 automobile design & engineering 02 engineering and technology Automotive engineering Comparative evaluation Financial engineering 0203 mechanical engineering Limit (music) Ecological potential Parametrization (atmospheric modeling) Relevance (information retrieval) 021108 energy Electrical and Electronic Engineering Software Civil and Structural Engineering |
| Zdroj: | Optimization and Engineering. 22:1001-1029 |
| ISSN: | 1573-2924 1389-4420 |
| DOI: | 10.1007/s11081-020-09539-2 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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