A Kalman Filter estimator for a Diesel Oxidation Catalyst during active regeneration of a CPF

Abstract

Estimating un-measurable states is an important component for onboard diagnostics (OBD) and control strategy development in diesel exhaust aftertreatment systems. This paper focuses on the development of an Extended Kalman Filter (EKF) based state estimator for a Diesel Oxidation Catalyst (DOC) during active regeneration of a catalyzed particulate filter (CPF). The DOC estimator is critical to predict the exhaust gas states entering the downstream aftertreatment components such as a CPF and NO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</sub> reduction catalysts such as urea-selective catalytic reduction (SCR) in heavy duty diesel vehicles. The internal states of the DOC that are important for the performance of the CPF and SCR systems include NO and NO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> concentration states, that participate in the passive oxidation of particulate matter (PM) in the CPF and that are important for urea injection control system design in the SCR catalyst. During CPF active regeneration, the DOC is used to achieve a temperature exotherm by oxidizing the injected diesel fuel resulting in hydrocarbon slip into the CPF and an increased CPF inlet temperature (550-600°C) which promotes the PM oxidation. The results show that HC and temperature states in the DOC can be estimated using an EKF estimator with NOx and temperature measurements upstream of the DOC and temperature measurements downstream of the DOC.