摘要
半径小于等于550 m的圆曲线路段是车辆易产生高碳排的路段。为揭示载重柴油车在这些小半径圆曲线路段的二氧化碳排放水平变化规律,以MOVES模型为基础,应用符合我国实际情况的道路、交通、车辆、燃油等信息,对MOVES模型中的参数做本地化修正及设置。通过采用MOVES模型进行载重柴油车碳排放模拟,得到了不同平面线形及行驶速度组合条件下的碳排量数据库。在此基础上,首先采用回归分析的方法分别建立了单位圆曲线长碳排量与圆曲线半径、圆曲线长度、车辆驶入圆曲线路段的初始速度3个参数的关系模型,其次采用迭代的方法建立了小半径圆曲线路段载重柴油车累积碳排放量预测模型。通过实地油耗试验,选用IPCC碳排放核算方法,将车辆油耗数据转换成碳排放数据,对比了碳排量核算值与模型预测值,验证了模型的预测精度。结果表明:单位圆曲线长碳排量以圆曲线半径、车辆驶入圆曲线路段的初始速度这2个参数分别为变量作二次函数形式的变化,以圆曲线长度为变量作幂函数形式的变化;累积碳排量以上述3个参数为变量作多元非线性函数形式的变化;经过参数本地化修正及设置的MOVES模型可以用于我国实际道路交通条件下的载重柴油车碳排放水平预测,以MOVES模拟为基础而建立的多元碳排量模型预测值与试验实测值的相对误差平均值为6. 02%,小于10%,具有较高的预测精度,可以在无需借助MOVES模型的情况下方便、快速地估算载重柴油车在小半径圆曲线路段的碳排量。
When the radius of a horizontal curve is no greater than 550 m,vehicles are prone to generate high carbon emissions. To reveal the rule of heavy-duty diesel trucks' carbon dioxide emissions on these smallradius curve sections,based on the MOVES model and using the information related to the road,traffic,vehicle,fuel,etc. in accordance with China ' s actual conditions,the parameters in MOVES model are modified and set through parameter localization. The carbon dioxide emissions of heavy-duty diesel trucks are simulated in MOVES,and a carbon emission database of different combinations of horizontal alignments and driving speeds is obtained. On this basis,first,regression analysis is used to establish the relational models between carbon emission per unit curve length and curve radius,curve length,initial speed of vehicle entering into curve respectively. Second,the iterative method is used to establish the prediction model of accumulated carbon emission of heavy-duty diesel trucks on small-radius curves. Through field fuelconsumption tests and IPCC carbon emission accounting method,the vehicle fuel consumption is converted into the calculated carbon emission,which is compared with the predicted carbon emission to verify the prediction accuracy. The result shows that(1) The carbon emission per unit curve length changes with the curve radius and initial speed of vehicle entering into curve in the forms of quadratic functions,and changes with the curve length in the form of power function.(2) The accumulated carbon emission changes with these3 parameters in the form of multivariate nonlinear function.(3) The MOVES model modified and set through parameter localization could be used to predict the carbon emission levels of heavy-duty diesel trucks under actual road and traffic conditions in China. The average relative error between the predicted value of the multivariate model,which is established based on MOVES simulation,and the experimental measured values is 6. 02%,less than 10%,which proves that the prediction model has a high prediction accuracy,and can be applied to estimate carbon emission of heavy-duty diesel trucks in small-radius curves conveniently and quickly without using the MOVES model.
引文
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