A statistical model of vehicle emissions and fuel consumption

A. Cappiello, I. Chabini, E. Nam, A. Lué, M. Abou Zeid
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引用次数: 248

Abstract

Many vehicle emission models am overly simple, such as the speed dependent models used widely, and other models are sufficiently complicated as to require excessive inputs and calculations, which can slow down computational time. We develop and implement an instantaneous statistical model of emissions (CO/sub 2/, CO, HC, and NOx) and fuel consumption for light duty vehicles, which is simplified from the physical load-based approaches that are gaining in popularity. The model is calibrated for a set of vehicles driven on standard as well as aggressive driving cycles. The model is validated on another driving cycle in order to, test its estimation capabilities. The preliminary results indicate that the model gives reasonable results compared to actual measurements as well as to results obtained with CMEM, a well-known load-based emission model. Furthermore, the results indicate that the model runs fast and is relatively simple to calibrate. The model presented can be integrated with a variety of traffic models to predict the spatial and temporal distribution of traffic emissions and assess the impact of ITS traffic management strategies on travel times, emissions, and fuel consumption.
车辆排放和燃料消耗的统计模型
许多车辆排放模型过于简单,如广泛使用的速度依赖模型,而其他模型则过于复杂,需要过多的输入和计算,这可能会减慢计算时间。我们开发并实施了轻型车辆排放(CO/sub 2/, CO, HC和NOx)和燃料消耗的即时统计模型,该模型从基于物理负载的方法中得到了简化,这种方法越来越受欢迎。该模型是为一组车辆的标准以及激进的驾驶周期进行校准。在另一个驾驶循环中验证了该模型,以测试其估计能力。初步结果表明,该模型与实际测量结果以及基于负荷的辐射模型CMEM的计算结果比较合理。结果表明,该模型运行速度快,校正相对简单。该模型可与多种交通模型集成,用于预测交通排放的时空分布,并评估ITS交通管理策略对出行时间、排放和燃料消耗的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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