Optimization data on total cost of ownership for conventional and battery electric heavy vehicles driven by humans and by automated driving systems
| Autor: | Leo Laine, Toheed Ghandriz, Jonas Hellgren, Bengt J H Jacobson |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Battery (electricity)
Automated driving systems Electrified propulsion Computer science Emerging technologies ComputerApplications_COMPUTERSINOTHERSYSTEMS Transportation Propulsion lcsh:Computer applications to medicine. Medical informatics Automotive engineering 03 medical and health sciences 0302 clinical medicine Engineering Range (aeronautics) Heavy vehicles Use case lcsh:Science (General) Productivity 030304 developmental biology 0303 health sciences Multidisciplinary Total cost of ownership Total cost of ownership data Fuel efficiency lcsh:R858-859.7 030217 neurology & neurosurgery lcsh:Q1-390 |
| Zdroj: | Data in Brief Data in Brief, Vol 30, Iss, Pp 105566-(2020) |
| ISSN: | 2352-3409 |
| Popis: | In road freight transport, the emerging technologies such as automated driving systems improve the mobility, productivity and fuel efficiency. However, the improved efficiency is not enough to meet environmental goals due to growing demands of transportation. Combining automated driving systems and electrified propulsion can substantially improve the road freight transport efficiency. However, the high cost of the battery electric heavy vehicles is a barrier hindering their adoption by the transportation companies. Automated driving systems, requiring no human driver on-board, make the battery electric heavy vehicles competitive to their conventional counterparts in a wider range of transportation tasks and use cases compared to the vehicles with human drivers. The presented data identify transportation tasks where the battery electric heavy vehicles driven by humans or by automated driving systems have lower cost of ownership than their conventional counterparts. The data were produced by optimizing the vehicle propulsion system together with the loading/unloading schemes and charging powers, with the objective of minimizing the total cost of ownership on 3072 different transportation scenarios, according to research article “Impact of automated driving systems on road freight transport and electrified propulsion of heavy vehicles” (Ghandriz et al., 2020) [2]. The data help understanding the effects of traveled distance, road hilliness and vehicle size on the total cost of ownership of the vehicles with different propulsion and driving systems. Data also include sensitivity tests on the uncertain parameters. |
| Databáze: | OpenAIRE |
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