Research output per year
Research output per year
Timo Melman*, David Abbink, Xavier Mouton, Adriana Tapus, Joost de Winter
Research output: Contribution to journal › Article › Scientific › peer-review
Current predictors of fuel consumption are typically based on computer simulations or data collections in real traffic, where the route and vehicle type are not under the researcher's control. Here, we predicted fuel consumption using test track data, an approach that allowed for location-specific predictions. Ninety-one drivers drove a total of 4617 laps, in two vehicles (Renault Mégane, Renault Clio), on two routes (highway and mountain), and with two eco-driving instructions (normal and eco). A multivariate analysis at the level of laps showed a strong predictive value for metrics related to speed, RPM, and throttle position, but with a considerable amount of variance attributable to route and vehicle type. A subsequent location-specific analysis showed that the predictive correlation of driving speed and throttle position fluctuated strongly during the lap and at some locations even became negative. We conclude that there is considerable potential in instantaneous location-specific prediction of fuel consumption.
Original language | English |
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Article number | 102627 |
Number of pages | 17 |
Journal | Transportation Research Part D: Transport and Environment |
Volume | 92 |
DOIs | |
Publication status | Published - 2021 |
Research output: Thesis › Dissertation (TU Delft)
Melman, T. (Creator), Abbink, D. A. (Creator), Mouton, X. (Creator), Tapus, A. (Creator) & de Winter, J. C. F. (Creator), TU Delft - 4TU.ResearchData, 5 Mar 2021
DOI: 10.4121/14139866
Dataset/Software: Dataset