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Optimization of a retrofit urea-SCR system.

机译:改造尿素-SCR系统的优化。

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摘要

Oxides of nitrogen (NOx) emissions from legacy diesel engines are often many times over currently mandated standards, contributing significantly to degradation of air quality and negative environmental impact. A retrofit urea-SCR (selective catalytic reduction) aftertreatment system offers a viable solution for reducing NOx emissions from older diesel engines. A stand-alone retrofit urea-SCR aftertreatment system was previously developed by West Virignia University (WVU) engineers, implementing a pre-SCR NOx sensor, open-loop feed-forward control, and stoichiometric NOx reduction logic. During experimental testing at WVU, the urea-SCR system demonstrated NOx reductions of 2% to 53%, depending on the test cycle. In order to optimize the system, this dissertation considered additional control configurations. To evaluate the emissions performance of each control strategy, a neural network heavy-duty diesel engine model was developed along with separate four-state chemical and thermal SCR catalyst models. Each model component was validated with experimental data recorded from the WVU Engine and Emissions Research Laboratory (EERL). The following control configurations were considered: (1) pre-SCR NOx sensor, open-loop feed-forward control, (2) post-SCR NOx sensor, closed-loop feed-back proportional-derivative (PD) control, (3) pre- and post-SCR NOx sensors, closed-loop feed-back proportional-integral-derivative (PID) control, (4) pre-SCR NOx sensor, model-based control.;The evaluation process considered differences between a highly instrumented and highly engineered system. Emissions performance was evaluated over two transient on-road test cycles (FTP, ACES HHDDT_S) and one steady-state marine test cycle (ICOMIA E5), implying broad applicability of the aftertreatment system. The evaluation process was characterized by overall NOx reduction percentage, maximum ammonia slip in parts per million (ppm), and average ammonia slip (ppm). The complexity of the sensor configuration and control strategy calibration were evaluated, as well as how adaptable a given configuration was to variations in engine behavior and sensor measurement accuracy. Finally, total cost was compared between each control configuration, considering system capital, maintenance, operation, control strategy engineering, and system calibration. A final cost per ton of NOx reduced was presented for each control configuration, assuming a six year operational cycle in marine and on-road applications. Based on the collective emissions, complexity, and cost analyses, a configuration implementing pre- and post-SCR NOx sensors and closed-loop PID control was identified as optimal for a retrofit application. Model results demonstrated NOx reductions of 44%, 53%, and 47% over FTP, ICOMIA, and ACES High-Speed Cruise (HHDDT_S) cycles, respectively. The total annual NOx reduction cost was
机译:传统柴油发动机排放的氮氧化物通常超过当前强制性标准的许多倍,极大地影响了空气质量的下降和对环境的负面影响。改造后的尿素-SCR(选择性催化还原)后处理系统为减少旧柴油机的NOx排放提供了可行的解决方案。西维里尼亚大学(WVU)工程师以前曾开发过一个独立的尿素-SCR后处理系统,该系统实现了SCR前NOx传感器,开环前馈控制和化学计量NOx还原逻辑。在WVU进行实验测试期间,根据测试周期的不同,尿素SCR系统的NOx排放量可减少2%至53%。为了优化系统,本文考虑了其他控制配置。为了评估每种控制策略的排放性能,开发了神经网络重型柴油机模型以及单独的四态化学和热SCR催化剂模型。每个模型组件均使用WVU发动机和排放研究实验室(EERL)记录的实验数据进行验证。考虑了以下控制配置:(1)SCR前NOx传感器,开环前馈控制,(2)SCR后NOx传感器,闭环反馈比例-微分(PD)控制,(3) SCR之前和之后的NOx传感器,闭环反馈比例积分微分(PID)控制,(4)SCR之前的NOx传感器,基于模型的控制;评估过程考虑了高度仪器化和高度工程化的系统。在两个瞬时道路测试周期(FTP,ACES HHDDT_S)和一个稳态海洋测试周期(ICOMIA E5)上评估了排放性能,这表明后处理系统具有广泛的适用性。评估过程的特征在于总的NOx还原百分比,最大的氨泄漏量(百万分之一)(ppm)和平均的氨泄漏量(ppm)。评估了传感器配置和控制策略校准的复杂性,以及给定配置对发动机性能和传感器测量精度变化的适应性。最后,比较了每种控制配置之间的总成本,其中考虑了系统资本,维护,操作,控制策略工程和系统校准。提出了每种控制配置的每吨NOx减排的最终成本,假设在船舶和道路应用中的运行周期为六年。基于总体排放,复杂性和成本分析,确定了采用SCR前和后SCR NOx传感器以及闭环PID控制的配置,是进行改装的最佳选择。模型结果表明,与FTP,ICOMIA和ACES高速巡航(HHDDT_S)循环相比,NOx分别减少了44%,53%和47%。每年减少NOx的总费用为

著录项

  • 作者

    Bedick, Clinton R.;

  • 作者单位

    West Virginia University.;

  • 授予单位 West Virginia University.;
  • 学科 Engineering Automotive.;Engineering Mechanical.;Engineering Chemical.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 209 p.
  • 总页数 209
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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