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Development of a heavy duty diesel vehicle emissions inventory prediction methodology.

机译:开发重型柴油车排放清单预测方法。

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摘要

Emissions from heavy-duty diesel vehicles are known to contribute a substantial fraction of the oxides of nitrogen (NOx), and particulate matter (PM) to the atmospheric inventory. Prediction of heavy-duty diesel vehicle emissions inventory is substantially less mature than the prediction of gasoline car emissions.; Heavy-duty truck emissions are affected by various parameters like vehicle weight/load, driving schedule used, and injection timing control strategies employed to operate the engine at more fuel-efficient (but higher NO x) mode.; Research has revealed a variety of options for inventory prediction, including the use of emissions factors based upon instantaneous engine power and instantaneous vehicle behavior. Effects of various parameters on the heavy-duty diesel emissions were studied in great detail and a speed-acceleration based emissions prediction approach was developed for heavy-duty diesel vehicle emissions prediction. A suite of emissions factor tables was generated for emissions inventory prediction. Driving schedules, vehicle weight, and off-cycle injection strategy were found to affect emissions to varying extents. Detailed analyses of a large body of data enabled to quantitatively as well as qualitatively characterize effect of various parameters on heavy duty diesel vehicle emissions. A doubling of vehicle weight was found to result in roughly a 50% increase in NOx emissions. The accuracy was found to improve with the inclusion of a large number of data covering wide range of model year groups and driving schedules.; Off-cycle operation was found to increase the NOx emissions by more than double. The speed-acceleration model predicted the emissions with reasonable accuracy.
机译:众所周知,重型柴油车辆的排放物在大气中占了氮氧化物(NOx)和颗粒物(PM)的大部分。重型柴油车排放清单的预测要比汽油车排放的预测要成熟得多。重型卡车的排放受到各种参数的影响,例如车辆重量/负载,使用的驾驶时间表以及为使发动机以更高燃油效率(但NOx更高)模式运行而采用的喷射正时控制策略。研究已经揭示了库存预测的多种选择,包括基于瞬时发动机功率和瞬时车辆行为使用排放因子。详细研究了各种参数对重型柴油车排放的影响,并开发了基于速度加速的排放量预测方法来预测重型柴油车的排放量。生成了一套排放因子表,用于排放清单预测。发现驾驶时间表,车辆重量和非循环喷射策略在不同程度上影响排放。对大量数据的详细分析使得能够定量和定性地表征各种参数对重型柴油车辆排放的影响。发现车辆重量加倍导致NOx排放量增加约50%。发现准确性的提高是因为包含了涵盖广泛的模型年份组和驾驶时间表的大量数据。发现非循环运行可使NOx排放增加两倍以上。速度加速模型可以合理地预测排放量。

著录项

  • 作者

    Gajendran, Prakash.;

  • 作者单位

    West Virginia University.;

  • 授予单位 West Virginia University.;
  • 学科 Engineering Automotive.; Engineering Mechanical.
  • 学位 Ph.D.
  • 年度 2005
  • 页码 189 p.
  • 总页数 189
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自动化技术及设备;机械、仪表工业;
  • 关键词

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