卡尔曼滤波器
估计员
扩展卡尔曼滤波器
计算机科学
控制理论(社会学)
统计
数学
人工智能
控制(管理)
作者
Harsha Shankar Surenahalli,Gordon G. Parker,John H. Johnson
摘要
<div class="section abstract"><div class="htmlview paragraph">This paper focuses on the development of an Extended Kalman Filter for estimating internal species concentration and storage states of an SCR using NO<sub>X</sub> and NH₃ sensors. The motivation for this work was twofold. First, knowledge of internal states may be useful for onboard diagnostic strategy development. In particular, significant errors between the outlet NO<sub>X</sub> or NH₃ sensors, reconstructed from estimated states, and the measured NO<sub>X</sub> or NH₃ concentrations may aid OBD strategies that attempt to identify particular system failure modes. Second, the EKF described estimates not only stored ammonia but also NO, NO₂ and NH₃ gas concentrations within and exiting the SCR. Exploiting knowledge of the individual species concentrations, instead of lumping them together as NO<sub>X</sub>, can yield improved closed loop urea controller performance in terms of reduced urea consumption and better NO<sub>X</sub> conversion.</div><div class="htmlview paragraph">The model used for EKF development was calibrated to transient engine data using a 2010 Cummins ISB engine with a production aftertreatment system consisting of a DOC, CPF and SCR. The EKF was then exercised for three different SCR outlets, sensor configurations: NO<sub>X</sub> only, NH₃ only and both NO<sub>X</sub> and NH₃. The EKF-estimated outlet NO, NO₂, and NH₃ concentrations were compared to measured experimental data using a mass spectrometer. Not surprisingly, the case where both NO<sub>X</sub> and NH₃ were measured at the SCR outlet and used as input to the EKF yielded the best results. The next best performance was achieved using only the NH₃ sensor. This was likely due to a better estimate of the NH₃ storage within the SCR and thus better estimates of the effect of the reactions. The results of the NO<sub>X</sub> sensor only case might be improved by using a better model of the NO<sub>X</sub> sensor.</div></div>
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