Design and experimental validation of an extended Kalman filter-based NOx concentration estimator in selective catalytic reduction system applications

This paper presents an extended Kalman filter (EKF) based approach of integrating NOx and NH3 sensors to estimate the NOx concentrations in Diesel engine selective catalytic reduction (SCR) aftertreatment systems. NOx sensors have been commonly used by vehicles for aftertreatment system control and onboard diagnostics (OBD) purposes. However, most currently available NOx 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 NOx sensors on urea-SCR systems where ammonia is the reductant for NOx conversions. Grounded in the insight into SCR dynamics and NOx sensor properties, a novel approach of using an extended Kalman filter to estimate the actual exhaust gas NOx concentration was proposed. The estimator was examined by NOx 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 NOx concentration measurements from the original NOx sensor readings.

Research Highlights
► This paper presents an extended Kalman filter for estimating NOx concentration.
► The estimator can address the NOx sensor cross-sensitivity to ammonia.
► The method can be applied for SCR system control and onboard diagnostics systems.