Model of Freight Vehicle Energy Consumption Based on Pearson Correlation Coefficient

Abstract

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.

Key words: highway transportation, energy consumption model, Pearson correlation coefficient, freight vehicles, key factor

摘要：

根据若干年货运车辆的调查数据，运用Pearson相关系数进行货运车辆单车百公里能耗的多元回归分析，通过相关程度确定了货运车辆百公里油耗的关键影响因子并量化了影响关系，借助二次回归结果构建单车百公里油耗模型，实现了货运车辆复杂因素下离散型油耗的高精度拟合.同时通过对北京市货运统计能耗对比和典型政策影响的案例分析，验证了对政策影响下各要素变量的响应，明确了车队能耗量化核算的准确度，并得到污染物减排政策下的货运能耗变化特征分析.本文研究为货运行业开展精细化能耗测算提供支撑.

关键词: 公路运输, 能耗模型, Pearson相关系数, 货运车辆, 关键因子

CLC Number:

U492.3+11

CAI Jing, ZHANG Ming-hui, ZHU Yu-ting, LIU Yu-huan. Model of Freight Vehicle Energy Consumption Based on Pearson Correlation Coefficient[J]. Journal of Transportation Systems Engineering and Information Technology, 2018, 18(5): 241-246.

蔡静，张明辉，朱宇婷，刘宇环. 基于Pearson相关系数的货运车辆能耗模型研究[J]. 交通运输系统工程与信息, 2018, 18(5): 241-246.

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URL: http://www.tseit.org.cn/EN/abstract/abstract19721.shtml

http://www.tseit.org.cn/EN/Y2018/V18/I5/241

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