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Transit bus load-based modal emission rate model development.

机译:基于公交客车负荷的模态排放率模型开发。

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摘要

Heavy-duty diesel vehicle (HDDV) operations are a major source of pollutant emissions in major metropolitan areas. Accurate estimation of heavy-duty diesel vehicle emissions is essential in air quality planning efforts because highway and non-road heavy-duty diesel emissions account for a significant fraction of the oxides of nitrogen (NOx) and particulate matter (PM) emissions inventories. Yet, major modeling deficiencies in the current MOBILE6 modeling approach for heavy-duty diesel vehicles have been widely recognized for more than ten years. While the most recent MOBILE6.2 model integrates marginal improvements to various internal conversion and correction factors, fundamental flaws inherent in the modeling approach still remain.; The major effort of this research is to develop a new heavy-duty vehicle load-based modal emission rate model that overcomes some of the limitations of existing models and emission rates prediction methods. This model is part of the proposed Heavy-Duty Diesel Vehicle Modal Emission Modeling (HDDV-MEM) which was developed by Georgia Institute of Technology. HDDV-MEM first predicts second-by-second engine power demand as a function of vehicle operating conditions and then applies brake-specific emission rates to these activity predictions.; To provide better estimates of microscopic level, this modeling approach is designed to predict second-by-second emissions from onroad vehicle operations. This research statistically analyzes the database provided by EPA and yields a model for prediction emissions at microscopic level based on engine power demand and driving mode. Research results will enhance the explaining ability of engine power demand on emissions and the importance of simulating engine power in real world applications. The modeling approach provides a significant improvement in HDDV emissions modeling compared to the current average speed cycle-based emissions models.
机译:重型柴油车(HDDV)的运行是主要都会区污染物排放的主要来源。准确估算重型柴油车的排放对于空气质量规划工作至关重要,因为高速公路和非公路用重型柴油的排放量占氮氧化物(NOx)和颗粒物(PM)排放清单的很大一部分。然而,十多年来,当前针对重型柴油车辆的MOBILE6建模方法中的主要建模缺陷已得到广泛认可。尽管最新的MOBILE6.2模型集成了对各种内部转换和校正因子的边际改进,但建模方法固有的基本缺陷仍然存在。这项研究的主要工作是开发一种新的基于重型车辆负荷的模态排放率模型,该模型克服了现有模型和排放率预测方法的某些局限性。该模型是佐治亚理工学院开发的拟议重型柴油机模态排放模型(HDDV-MEM)的一部分。 HDDV-MEM首先根据车辆工况预测每秒的发动机功率需求,然后将制动器特定的排放率应用于这些活动预测。为了提供更好的微观水平估算,此建模方法旨在预测道路车辆运行产生的每秒排放。这项研究对EPA提供的数据库进行了统计分析,并基于发动机的动力需求和驾驶模式,建立了微观水平的排放预测模型。研究结果将增强对排放的发动机动力需求的解释能力,以及在实际应用中模拟发动机动力的重要性。与当前基于平均速度周期的排放模型相比,该建模方法显着改善了HDDV排放模型。

著录项

  • 作者

    Feng, Chunxia.;

  • 作者单位

    Georgia Institute of Technology.;

  • 授予单位 Georgia Institute of Technology.;
  • 学科 Engineering Civil.; Engineering Environmental.
  • 学位 Ph.D.
  • 年度 2007
  • 页码 349 p.
  • 总页数 349
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 建筑科学;环境污染及其防治;
  • 关键词

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