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Modelling of NO_X emission factors from heavy and light-duty vehicles equipped with advanced aftertreatment systems

机译:配备先进后处理系统的重型和轻型车辆的NO_X排放因子模型

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摘要

NO, emission standards are becoming stringiest over the world especially for heavy-duty vehicles. To comply with current and future regulations some vehicle manufacturers are adopting exhaust aftertreatment systems known as Selective Catalytic Reduction (SCR). The catalysts are based on Vanadium (Va) and the reductant agent based on ammonia. However, Va is listed on the California Proposition 65 List as potentially causing cancer and alternatives are being studied. This paper presents a model based on neural networks that integrated with a road vehicle simulator allows to estimate NO, emission factors for different powertrain configurations, along different driving conditions, and covering commercial, zeolite and mordenite alternatives as the base monolith for SCR. The research included the experimental study of copper based and iron based zeolites (ZSM5 and Cuban natural mordenite). The response of NO_x conversion efficiency was monitored in a laboratory for varying space velocity, oxygen, sulphur, water, NO_x and SO_2 emulating the conditions of a Diesel engine exhaust along a trip. The experimental data was used for training neural networks and obtaining a mathematical correlation between the outputs and inputs of the SCR system. The developed correlation was integrated with ADVISOR road vehicle simulator to obtain NO_x emission factors and to test each SCR system installed on light-duty and heavy-duty vehicles for standardized driving cycles and real measured driving cycles. Despite having lower NO_x conversion efficiencies than the CATCO in the ETC/ESC and NEDC cycles, FeZSM5 maintain the Euro regulation level. Therefore FeZSM5 can be a possible candidate as far as pollutants regulation is considered.
机译:不,排放标准在世界范围内越来越严格,尤其是重型车辆。为了符合当前和将来的法规,一些汽车制造商正在采用称为选择性催化还原(SCR)的排气后处理系统。催化剂基于钒(Va),还原剂基于氨。但是,Va被列为“加州65号提案”中的潜在致癌物质,正在研究替代方法。本文提出了一个基于神经网络的模型,该模型与道路车辆模拟器集成在一起,可以估算不同动力总成配置,不同驾驶条件下的NO排放因子,并涵盖了商业,沸石和丝光沸石替代品,作为SCR的基础。研究包括铜基和铁基沸石(ZSM5和古巴天然丝光沸石)的实验研究。在实验室中监测了NO_x转化效率的响应,以模拟空燃比,沿行程的空速,氧气,硫,水,NO_x和SO_2的变化。实验数据用于训练神经网络,并获得SCR系统的输出和输入之间的数学相关性。所开发的相关性与ADVISOR道路车辆模拟器集成在一起,以获取NO_x排放因子,并测试安装在轻型和重型车辆上的每个SCR系统的标准化驾驶循环和实际测得的驾驶循环。尽管在ETC / ESC和NEDC循环中NO_x转化效率低于CATCO,但FeZSM5仍保持欧洲法规水平。因此,就污染物法规而言,FeZSM5可能是候选者。

著录项

  • 来源
    《Energy Conversion & Management》 |2011年第9期|p.2945-2951|共7页
  • 作者单位

    IDMEC - Institute of Mechanical Engineering, Instituta Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon, Portugal;

    IDMEC - Institute of Mechanical Engineering, Instituta Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon, Portugal;

    Departamento de Qulmica Inorganka, Cristalografia y Mineralogia, Unidad Asociada al Instituto de Catalisis, CSIC, Universidad de Malaga, Campus de Teatinos, 29071 Malaga, Spain;

    IDMEC - Institute of Mechanical Engineering, Instituta Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon, Portugal;

    IDMEC - Institute of Mechanical Engineering, Instituta Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon, Portugal,Departamento de Qulmica Inorganka, Cristalografia y Mineralogia, Unidad Asociada al Instituto de Catalisis, CSIC, Universidad de Malaga, Campus de Teatinos, 29071 Malaga, Spain;

    Departamento de Qulmica Inorganka, Cristalografia y Mineralogia, Unidad Asociada al Instituto de Catalisis, CSIC, Universidad de Malaga, Campus de Teatinos, 29071 Malaga, Spain;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    scr no; diesel road vehicle zeolites neural-networks road vehicle simulator;

    机译:SCR号;柴油道路车辆沸石神经网络道路车辆模拟器;

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