Design and experimental validation of an extended Kalman filter-based NO x concentration estimator in selective catalytic reduction system applications

Abstract

This paper presents an extended Kalman filter (EKF) based approach of integrating NO x and NH 3 sensors to estimate the NO x concentrations in Diesel engine selective catalytic reduction (SCR) aftertreatment systems. NO x sensors have been commonly used by vehicles for aftertreatment system control and onboard diagnostics (OBD) purposes. However, most currently available NO x sensors are cross-sensitive to ammonia. Based on the experimental observations and physical inferences, the cross-sensitivity characteristics may change with temperature and is hard to be predicted by a model. This feature limits the applications of NO x sensors on urea-SCR systems where ammonia is the reductant for NO x conversions. Grounded in the insight into SCR dynamics and NO x sensor properties, a novel approach of using an extended Kalman filter to estimate the actual exhaust gas NO x concentration was proposed. The estimator was examined by NO x measurements from a Horiba gas analyzer under different engine operating conditions. The experimental results show that the EKF-based approach can significantly improve the accuracy of NO x concentration measurements from the original NO x sensor readings.