Prediction of NOX Vehicular Emissions using On-Board Measurement and Chassis Dynamometer Testing

Motor vehicles’ rate models for predicting emissions of oxides of nitrogen (NOX ) are insensitive to their modes of operation such as cruise, acceleration, deceleration and idle, because these models are usually based on the average trip speed. This study demonstrates the feasibility of using other variables such as vehicle speed, acceleration, load, power and ambient temperature to predict NOX emissions. The NOX emissions need to be accurately estimated to ensure that air quality plans are designed and implemented appropriately. For this, we propose to use the non-parametric multivariate adaptive regression splines (MARS) to model NOX emission of vehicle in accordance with on-board measurements and also the chassis dynamometer testing. The MARS methodology is then applied to estimate the NOX emissions. The model approach provides more reliable results of the estimation and offers better predictions of NOX emissions. The results therefore suggest that the MARS methodology is a useful and fairly accurate tool for predicting NOX emission that may be adopted by regulatory agencies in understanding the effect of vehicle operation and NOX emissions.