NO and NO2 Concentration Modeling and Observer-Based Estimation Across a Diesel Engine Aftertreatment System

Abstract

This paper presents an experimentally validated control-oriented model and an observer for diesel oxidation catalyst (DOC)-diesel particulate filter (DPF) system in the context of exhaust gas NO and NO2 concentration estimations. NO and NO2 have different reaction characteristics within DPF and selective catalytic reduction (SCR) systems, two most promising diesel engine aftertreatment systems. Although the majority of diesel engine-out NOx emissions is NO, the commonly used DOC located upstream of a DPF and a SCR can convert a considerable amount of NO to NO2. Knowledge of the NO/NO2 ratio in exhaust gas is thus meaningful for the control and diagnosis of DPF and SCR systems. Existing onboard NOx sensors cannot differentiate NO and NO2, and such a sensory deficiency makes separate considerations of NO and NO2 in SCR control design challenging. To tackle this problem, a control-oriented dynamic model, which can capture the main NO and NO2 dynamics from engine-out, through DOC, and to DPF, was developed. Due to the computational limitation concerns, DOC and DPF are assumed to be standard continuously stirred tank reactors in order to obtain a 0D ordinary differential equation model. Based on the model, an observer, with the measurement from a commercially available NOx sensor, was designed to estimate the NO and NO2 concentrations in the exhaust gas along the aftertreatment systems. The stability of the observer was shown through a Lyapunov analysis assisted by insight into the system characteristics. The control-oriented model and the observer were validated with engine experimental data and the measured NO/NO2 concentrations by a Horiba gas analyzer. Experimental results show that the model can accurately predict the main engine-out/DOC/DPF NO/NO2 dynamics very well in semisteady-state tests. For the proposed observer, the predictions converge to the model values and estimate the NO and NO2 concentrations in the aftertreatment system well.