Study on a Prediction Model of Superhighway Fuel Consumption Based on the Test of Easy Car Platform

Yong-Ming He, Jia Kang, Yu-Long Pei, Bin Ran and Yu-Ting Song
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Yong-Ming He: School of Transportation, Northeast Forestry University, 26 Hexing Road, Harbin 150040, China
Jia Kang: School of Transportation, Northeast Forestry University, 26 Hexing Road, Harbin 150040, China
Yu-Long Pei: School of Transportation, Northeast Forestry University, 26 Hexing Road, Harbin 150040, China
Bin Ran: School of Civil Engineering, University of Wisconsin-Madison, Madison, WI 57305, USA
Yu-Ting Song: School of Transportation, Northeast Forestry University, 26 Hexing Road, Harbin 150040, China

Sustainability, 2020, vol. 12, issue 15, 1-19

Abstract: To explore the relationship between fuel consumption and speed for a vehicle on a superhighway with a design speed exceeding 120 km/h, the fuel consumption data provided by the Test of Easy Car platform are used to fit the fuel consumption of different models. The fitting results show that the fitting degree of fuel consumption by a cubic curve is the highest, and the correlation coefficient is above 0.95. A fuel consumption cubic curve model of different vehicle types is established by using the fitting parameters to predict the fuel consumption when a vehicle is running at a speed of 130 km/h–180 km/h. The prediction results show that the average fuel consumption of compact vehicles is the lowest when a vehicle is running on a superhighway at speeds of 130 km/h–180 km/h, with values of 8.95 L/100 km–16.26 L/100 km; the average fuel consumption of sport utility vehicles (SUVs) is the highest, with values of 12.65 L/100 km–22.70 L/100 km. The prediction results can be used to estimate the cost of using a superhighway and provide a basis for estimating the feasibility of superhighways.

Keywords: superhighway; constant-speed fuel consumption; curve fitting; prediction model; comparative analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
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