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Sensitivity Analysis for MOVES Running Emission: A Latin Hypercube Sampling-based Approach

机译:MOVES运行排放的灵敏度分析:基于拉丁超立方采样的方法

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In order to interpret how the uncertainty in the output can be apportioned to different sources of uncertainty in its inputs, it is critical to understand the MOVES model sensitivity. In this research, the MOVES model project level sensitivity tests on running emission were conducted thru the analysis of vehicle specific power, scaled tractive power, and MOVES emission rates versus speed curves. This study tested the speed, acceleration, and grade - three most critical variables for vehicle specific power for light duty vehicles and scaled tractive power for heavy duty vehicles. A Latin Hypercube sampling based method for estimation of the "Sobal" sensitivity indices showed that the speed is the most critical variable among the three inputs for both VSP and STP. Acceleration and grades showed lower response to the main effects and sensitivity indices. No significant differences on emissions rates among the regulatory classes of heavy duty vehicles were identified.
机译:为了解释如何将输出不确定性分配给输入不确定性的不同来源,理解MOVES模型的敏感性至关重要。在这项研究中,通过分析车辆的比功率,按比例绘制的牵引功率以及MOVES排放速率与速度曲线,对运行排放进行了MOVES模型项目级灵敏度测试。这项研究测试了速度,加速度和坡度-轻型车辆的车辆特定功率和重型车辆的比例牵引功率的三个最关键变量。基于拉丁Hypercube采样的估算“ Sobal”灵敏度指数的方法表明,对于VSP和STP,速度是三个输入中最关键的变量。加速度和等级显示出对主要效果和灵敏度指标的响应较低。在重型车辆的监管类别之间,没有发现排放率的显着差异。

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