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Experimental Validation of an Unscented Kalman Filter for Estimating Transient Engine Exhaust Composition with Fourier Transform Infrared Spectroscopy

机译:无味卡尔曼滤波器用于傅立叶变换红外光谱估计瞬态发动机排气成分的实验验证

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摘要

Fourier transform infrared (FTIR) spectroscopy is a prevalent technique for measuring the comprehensive chemical composition of engine emissions. However, its applicability to transient emissions is limited due to recirculation of exhaust from past engine cycles within a FTIR gas cell and nonstationarity of the infrared beam intensity. An unscented Kalman filter is developed to overcome these limitations and obtain accurate, time-resolved estimations of engine exhaust composition from FTIR measurements. Residence time distribution within the FTIR gas cell is modeled using the well-mixed assumption, while the Fourier transform of an interferogram generated from a linearly evolving, uniformly broadened absorption line is used to deduce transient gas cell composition values from FTIR measurements. The filter utilizes both models, as well as measurement noise statistics, to infer the composition of sample entering the FTIR gas cell during a measurement period. To validate the filter, FTIR measurements of air with transient, trace amounts of acetylene are conducted. A variety of composition profiles are explored with different combinations of composition standard deviation (15 and 45 ppm) and duration between set points (0.4 and 1 s). The results demonstrate that measurement noise becomes less impactful as the magnitudes of composition fluctuations increase, while residence time effects become less significant as the duration of fluctuations increase. Improvements in estimated composition are achieved by the filter in every case, with an average improvement of 32% over unfiltered FTIR measurements. Experiments are conducted using sample flow rates of 12 and 25 standard liters per minute. More accurate measurements and estimations are attained at higher sample flow rates, highlighting the importance of maximizing flow rate to reduce residence time effects for transient measurements.
机译:傅立叶变换红外(FTIR)光谱是一种用于测量发动机排放物的综合化学成分的流行技术。然而,由于来自FTIR气室中过去发动机循环的废气的再循环以及红外光束强度的不稳定性,其对瞬态排放的适用性受到限制。开发了无味的卡尔曼滤波器来克服这些限制,并通过FTIR测量获得准确,时间分辨的发动机排气成分估计。 FTIR气室中的停留时间分布是使用充分混合的假设进行建模的,而从线性演化,均匀加宽的吸收线生成的干涉图的傅立叶变换可用于从FTIR测量中推断出瞬态气室组成值。该过滤器利用这两种模型以及测量噪声统计数据来推断在测量期间进入FTIR气室的样品的成分。为了验证过滤器,对空气进行了瞬态,痕量乙炔的FTIR测量。利用组成标准偏差(15和45 ppm)和设定点之间的持续时间(0.4和1 s)的不同组合,探索了各种组成曲线。结果表明,随着成分波动幅度的增加,测量噪声的影响减小,而随着波动持续时间的增加,停留时间的影响变得不那么明显。在每种情况下,滤波器均可实现估计成分的改进,与未过滤的FTIR测量值相比,平均可提高32%。使用每分钟12和25标准升的样品流速进行实验。在更高的样品流速下可以获得更准确的测量和估计,突出了最大化流速以减少瞬态测量的停留时间影响的重要性。

著录项

  • 来源
    《Energy & fuels》 |2018年第11期|11899-11912|共14页
  • 作者

    Wilson David; Allen Casey;

  • 作者单位

    Marquette Univ, Dept Mech Engn, Milwaukee, WI 53233 USA;

    Marquette Univ, Dept Mech Engn, Milwaukee, WI 53233 USA;

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

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