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Author:

Cai, Jing (Cai, Jing.) | Zhang, Ming-Hui (Zhang, Ming-Hui.) | Zhu, Yu-Ting (Zhu, Yu-Ting.) | Liu, Yu-Huan (Liu, Yu-Huan.)

Indexed by:

EI Scopus CSCD

Abstract:

Based on the survey data of freight vehicles for several years, this paper carries out the multiple regression analysis on 100 km energy consumption of single-vehicles by Pearson correlation coefficient and determines three key influence factors of the fuel consumption per hundred kilometers of freight vehicles by related degree, and quantify every factor's effect. Using the results of the quadratic regression to establish 100 km fuel consumption model for single vehicle, the high-precision fitting of discrete fuel consumption of freight vehicles is achieved under the complex factors. Meanwhile, after compared with Beijing's freight statistics on energy consumption and analyzed the typical cases under the impact of policies, the response to each factor variable under the influence of policies is verified, the accuracy of quantitative calculation of fleet energy consumption is defined, and the analysis on the variation characteristics of freight energy consumption under pollutant emission reduction policy is obtained, which provides the support for the refined energy consumption measurement and calculation in freight industry. Copyright © 2018 by Science Press.

Keyword:

Systems engineering Energy policy Motor transportation Freight cars Factor analysis Correlation methods Emission control Fuels Vehicles Regression analysis Energy utilization

Author Community:

  • [ 1 ] [Cai, Jing]Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Cai, Jing]Beijing Transport Institute, Beijing; 100073, China
  • [ 3 ] [Zhang, Ming-Hui]Beijing Transport Institute, Beijing; 100073, China
  • [ 4 ] [Zhu, Yu-Ting]Beijing Transport Institute, Beijing; 100073, China
  • [ 5 ] [Liu, Yu-Huan]Beijing Transport Institute, Beijing; 100073, China

Reprint Author's Address:

  • [cai, jing]beijing transport institute, beijing; 100073, china;;[cai, jing]beijing university of technology, beijing; 100124, china

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Source :

Journal of Transportation Systems Engineering and Information Technology

ISSN: 1009-6744

Year: 2018

Issue: 5

Volume: 18

Page: 241-246

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 11

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 17

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