Prediction of NO _x Emissions of a Heavy Duty Diesel Engine with a NLARX Model

This work describes the application of Non-Linear Autoregressive Models with Exogenous Inputs (NLARX) in order to predict the NO_x emissions of heavy-duty diesel engines. Two experiments are presented: 1.) a Non-Road-Transient-Cycle (NRTC) 2.) a composition of different engine operation modes and different engine calibrations. Data sets are pre-processed by normalization and re-arranged into training and validation sets. The chosen model is taken from the MATLAB Neural Network Toolbox using the algorithms provided. It is teacher forced trained and then validated. Training results show recognizable performance. However, the validation shows the potential of the chosen method.