轻型车速度与坡度对排放影响的耦合关系

doi:10.13229/j.cnki.jdxbgxb.20250496

Abstract

Abstract:

Based on one-year， second-by-second on-board diagnostic（OBD） monitoring data from 10 light-duty vehicles in Xi'an， road slopes were extracted by combining high-resolution digital elevation models（DEMs） with geographic information system（GIS） path-matching techniques. Vehicle-specific power（VSP） theory and the Motor Vehicle Emission Simulator（MOVES） model were employed to estimate emissions of carbon monoxide（CO）， hydrocarbons（HC）， nitrogen oxides（NO _x ）， and particulate matter（PM）. To address the limitations of conventional models in capturing the coupled effects of speed and slope， a bivariate polynomial regression model of speed-slope was developed， and an uphill-downhill partitioning strategy was applied to analyze the nonlinear characteristics of emissions. Results show that the proposed model achieves coefficient of determination（R²） values exceeding 0.82， with favorable error metrics. Specifically， emissions of all pollutants increase significantly with speed and slope under uphill conditions， whereas downhill operations exhibit generally lower emissions but with local peak values. Moreover， three-dimensional response surfaces indicate that HC and NO _x are more sensitive to variations in operating conditions. This study provides a high-resolution quantification of the speed-slope-emission relationship， offering theoretical and empirical support for accurate urban micro-scale emission estimation， driving condition identification， and traffic-related emission reduction strategies.

Key words: vehicle operation engineering, light-duty vehicle emissions, speed-slope coupling, second-order polynomial regression, vehicle specific power

CLC Number:

U491.9

Yang YANG,Jia-xing HOU,Qian YU. Coupling effect of speed and road slope on emissions from light-duty vehicles[J].Journal of Jilin University(Engineering and Technology Edition), 2026, 56(10): 2626-2634.

Figures/Tables 7

Fig.1

Fig.2

Table 1

Fitting results under uphill and downhill segmentation"

坡度	拟合参数污染物	$β 0$	$β 1$	$β 2$	$β 3$	$β 4$	$β 5$
上坡	CO	-8.136 259	0.090 081	-32.679 764	-0.000 503	294.788 948	0.399 979
	HC	-10.674 830	0.072 107	-27.586 534	-0.000 388	270.228 294	0.320 825
	NO _x	-10.962 125	0.083 527	-31.634 116	-0.000 462	312.719 588	0.363 534
	PM	-13.330 739	0.077 097	-27.085 290	-0.000 418	252.867 415	0.333 062
下坡	CO	-8.256 284	0.095 792	21.229 739	-0.000 556	359.042 699	0.028 730
	HC	-10.695 886	0.073 384	20.691 560	-0.000 402	308.620 937	-0.049 474
	NO _x	-11.419 067	0.109 939	25.057 602	-0.000 765	176.803 097	-0.393 384
	PM	-13.396 741	0.080 445	18.380 008	-0.000 450	292.933 563	0.001 800

Table 1

Table 2

Performance evaluation metrics of prediction models for various pollutants"

坡度	评估指标污染物	R²	MSE	RMSE	MAE
上坡	CO	0.857 3	0.002 395	0.048 938	0.004 019
	HC	0.872 3	5× $10 - 6$	0.002 210	1.54× $10 - 4$
	NO _x	0.859 8	5× $10 - 6$	0.002 241	1.79× $10 - 4$
	PM	0.868 9	1× $10 - 7$	0.000 181	1.4× $10 - 6$
下坡	CO	0.824 7	0.000 595	0.024 400	0.002 946
	HC	0.854 2	1× $10 - 6$	0.001 000	1.06× $10 - 4$
	NO _x	0.859 1	1× $10 - 6$	0.001 113	1.30× $10 - 4$
	PM	0.843 5	1× $10 - 7$	0.000 086	1× $10 - 5$

Table 2

Table 3

Averaged performance metrics of pollutant prediction models via K-fold cross- validation"

坡度	评估指标污染物	R²	MSE	RMSE	MAE
上坡	CO	0.842 8	0.002 395	0.047 853	0.004 019
	HC	0.852 2	5× $10 - 6$	0.002 090	1.54× $10 - 4$
	NO _x	0.845 0	5× $10 - 6$	0.002 184	1.79× $10 - 4$
	PM	0.850 5	1× $10 - 7$	0.000 174	1.4× $10 - 6$
下坡	CO	0.824 7	5.95× $10 - 6$	0.023 839	0.002 946
	HC	0.854 1	1× $10 - 6$	0.000 966	1.06× $10 - 4$
	NO _x	0.827 9	1× $10 - 6$	0.001 095	1.30× $10 - 4$
	PM	0.843 5	1× $10 - 7$	0.000 083	1× $10 - 5$

Table 3

Fig.3

Table 4

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污染物	运行工况	峰值排放量/（g·s^-1）	峰值速度/ （km·h^-1）	峰值坡度/%
CO	上坡	0.029 57	77.58	5
CO	下坡	0.015 8	80	接近0
HC	上坡	0.001 7	113.95	5
HC	下坡	0.000 64	92.13	接近0
NO _x	上坡	0.002 1	109.1	5
NO _x	下坡	0.000 74	87.28	接近0
PM	上坡	0.000 15	111.53	5
PM	下坡	0.000 06	89.71	接近0

Coupling effect of speed and road slope on emissions from light-duty vehicles

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