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World Electric Vehicle Journal is published by MDPI from Volume 9 issue 1 (2018). Articles in this Issue were published by The World Electric Vehicle Association (WEVA) and its member the European Association for e-Mobility (AVERE), the Electric Drive Transportation Association (EDTA), and the Electric Vehicle Association of Asia Pacific (EVAAP). They are hosted by MDPI on as a courtesy and upon agreement with AVERE.
Open AccessArticle

Energy Consumption Prediction of a Vehicle along a User-Specified Real-World Trip

Argonne National Laboratory
NAVTEQ North America
Author to whom correspondence should be addressed.
World Electr. Veh. J. 2012, 5(4), 1109-1120;
Published: 28 December 2012
PDF [1378 KB, uploaded 18 May 2018]


Standard cycles provide an easy way to evaluate the energy consumption of vehicles, but it is the energy consumption that occurs on real-world trips that really matters to the driver and, to a larger extent, society. This study shows how digital maps and vehicle simulation tools can be used to estimate energy consumption on a real-world trip. The user (1) selects a trip in the mapping service ADAS-RP (Advanced Driver Assistance Systems Research Platform), (2) defines a vehicle model in the vehicle powertrain simulation tool Autonomie, and (3) runs and analyzes the simulation in that same tool. For each section of the trip, ADAS-RP provides various information that can include speed limits, historic data on traffic pattern speeds, the slopes of the routes, and the positions of stop signs and traffic lights. The first stage of processing this information is to schedule the stops and to create an intermediate speed target that takes those stops into account. The final driver demand speed includes transitions – accelerations and decelerations – between sections with different intermediate speed targets, or around stops. The ADAS-RP/Autonomie process is then used to compute the energy consumption of a hybrid electric vehicle and a conventional vehicle on 10 trips defined across the United States and Germany. The hybrid vehicle is more fuel efficient, especially on congested routes and routes with downhill slopes, the effect of which is analyzed in further detail.
Keywords: vehicle simulation; trip prediction; geographic information system (GIS) vehicle simulation; trip prediction; geographic information system (GIS)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Karbowski, D.; Pagerit, S.; Calkins, A. Energy Consumption Prediction of a Vehicle along a User-Specified Real-World Trip. World Electr. Veh. J. 2012, 5, 1109-1120.

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