Harnessing Big Data for Estimating the Energy Consumption and Driving Range of Electric Vehicles
Analyzing the factors that affect the energy efficiency of vehicles is crucial to the overall improvement of the environmental efficiency of the transport sector, one of the top polluting sectors at the global level. This study analyzes the energy consumption rate (ECR) and driving range (DR) of battery electric vehicles (BEVs) and provides insight into the factors that affect their energy consumption by harnessing big data from real-world driving. The analysis relied on four data sources: (i) driving patterns collected from 741 drivers over a two-year period; (ii) drivers’ characteristics; (iii) road type; (iv) weather conditions. The results of the analysis measure the mean ECR of BEVs at 0.183 kWh/km, underline a 34% increase in ECR and a 25% decrease in DR in the winter with respect to the summer, and suggest the electricity tariff for BEVs to be cost efficient with respect to conventional ones. Moreover, the results of the analysis show that driving speed, acceleration and temperature have non-linear effects on the ECR, while season and precipitation level have a strong linear effect. The econometric model of the ECR of BEVs suggests that the optimal driving speed is between 45 and 56 km/h and the ideal temperature from an energy efficiency perspective is 14 °C. Clearly, the performance of BEVs highly depends on the driving environment, the driving patterns, and the weather conditions, and the findings from this study enlighten the consumers to be more informed and manufacturers to be more aware of the actual utilization of BEVs.
-
Supplemental Notes:
- This paper was sponsored by TRB committee ADC70 Standing Committee on Transportation Energy.
-
Corporate Authors:
500 Fifth Street, NW
Washington, DC United States 20001 -
Authors:
- Fetene, Gebeyehu M
- Kaplan, Sigal
- Mabit, Stefan L
- Jensen, Anders F
- Prato, Carlo G
-
Conference:
- Transportation Research Board 95th Annual Meeting
- Location: Washington DC, United States
- Date: 2016-1-10 to 2016-1-14
- Date: 2016
Language
- English
Media Info
- Media Type: Digital/other
- Features: Figures; References; Tables;
- Pagination: 19p
- Monograph Title: TRB 95th Annual Meeting Compendium of Papers
Subject/Index Terms
- TRT Terms: Data analysis; Driving; Electric vehicles; Energy consumption; Pollutants; Vehicle performance; Vehicle range
- Subject Areas: Data and Information Technology; Environment; Highways; Vehicles and Equipment; I15: Environment; I91: Vehicle Design and Safety;
Filing Info
- Accession Number: 01587905
- Record Type: Publication
- Report/Paper Numbers: 16-2689
- Files: TRIS, TRB, ATRI
- Created Date: Jan 27 2016 5:12PM