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首页> 外文期刊>Journal of Dynamic Systems, Measurement, and Control >Oxygen Concentration Dynamic Model and Observer-Based Estimation Through a Diesel Engine Aftertreatment System
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Oxygen Concentration Dynamic Model and Observer-Based Estimation Through a Diesel Engine Aftertreatment System

机译:柴油机后处理系统中氧浓度动态模型和基于观测器的估计

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摘要

Due to the chemical reactions occurring inside the diesel oxidation catalysts (DOCs) and diesel particulate filters (DPFs) that are commonly equipped on diesel engines, the exhaust gas oxygen concentrations considerably vary through the aftertreatment systems. Oxygen concentration in exhaust gas is important for the performance of catalysts such as the NO_x conversion efficiencies of the selective catalytic reduction systems and lean NO_x traps. Moreover, in the presence of a low-pressure loop exhaust gas recirculation, the exhaust gas oxygen concentration after DPF also influences the in-cylinder combustion. From system control, estimation, and analysis viewpoints, it is thus imperative to have a control-oriented model to describe the oxygen concentration dynamics across the DOC and DPF. In this paper, a physics-based, lumped-parameter, control-oriented DOC-DPF oxygen concentration dynamic model was developed with a multi-objective optimization method and validated with the experimental data obtained on a medium-duty diesel engine equipped with a full suite of aftertreatment systems. Experimental results show that the model can well capture the oxygen dynamics across the diesel engine aftertreatment systems. As an application of the experimentally validated model, an observer was designed to estimate the DOC-out and DPF-out oxygen concentrations in real time. Experimental results show that the estimated states from the proposed observer can converge to the measured signals fastly and accurately.
机译:由于通常安装在柴油发动机上的柴油氧化催化剂(DOC)和柴油微粒过滤器(DPF)内部发生化学反应,因此废气中的氧气浓度会在后处理系统中发生很大变化。废气中的氧气浓度对于催化剂的性能非常重要,例如选择性催化还原系统的NO_x转化效率和稀薄的NO_x捕集阱。此外,在存在低压回路排气再循环的情况下,DPF之后的排气氧浓度也影响缸内燃烧。从系统控制,估计和分析的观点来看,因此必须有一个面向控制的模型来描述整个DOC和DPF的氧气浓度动态。本文采用多目标优化方法建立了基于物理的,集总参数,面向控制的DOC-DPF氧气浓度动态模型,并使用装备了全功能柴油机的中型柴油机的实验数据进行了验证一套后处理系统。实验结果表明,该模型可以很好地捕获整个柴油发动机后处理系统中的氧气动力学。作为经过实验验证的模型的应用,设计了一个观察器来实时估计DOC-out和DPF-out的氧气浓度。实验结果表明,提出的观测器的估计状态可以快速,准确地收敛到测量信号。

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