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 NOx conversion efficiencies of the selective catalytic reduction systems and lean NOx 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.

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