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The interest for NOx estimators (also known as virtual sensors or inferential sensors) has increased over the recent years due to benefits attributed to cost and performance. NOx estimators are typically installed to improve On-Board Diagnostics (OBD) monitors or to lower bill of material costs by replacing physical NOx sensors. This paper presents initial development results of a virtual engine-out NOx estimator planned for the implementation on an ECM. The presented estimator consists of an airpath observer and a NOx combustion model. The role of the airpath observer is to provide input values for the NOx combustion model such as the states of the gas at the intake and exhaust manifolds. It contains a nonlinear mean-value model of the airpath suitably transformed for an efficient and robust implementation on an ECM. The airpath model uses available sensory information in the vehicle to correct predictions of the gas states.

Recently, numerous researchers and Original Equipment Manufacturers (OEMs) have developed diesel engine-out nitrogen oxides (NOx) estimation algorithms that are capable of running in real-time on production Electronic Control Units (ECUs). These are generally referred to as virtual sensors or inferential sensors. NOx estimators are typically installed to improve On-Board Diagnostics (OBD) monitors or to lower bill of material costs by replacing physical NOx sensors. This paper reviews the literature of on-ECU NOx models in order to document the state of the art and identify directions for future work. The discussion includes applications of NOx estimators, accuracy of NOx estimators, required sensor inputs, sources of error, calibration effort, and ECU resource consumption.