Over a significant period of time, efforts have been made towards a valid and accurate estimation of DI diesel engine NOx emissions. Considering the fact that experiments have a high cost in both time and money, modelling approaches have been developed in an effort to overcome these issues. It is well known that accuracy in the prediction of NOx emissions lies specifically on the accurate estimation of local temperature and O2 histories inside the combustion chamber that govern NOx formation, fulfilled by an accurate estimation of the combustion mechanism. To account for the actual effect of parameters that control NOx formation and overcome inefficiencies introduced from existing purely empirical models or artificial neural networks, valid only on the combustion systems for which they were developed [1], an alternative solution is the introduction of physically based semi-empirical models. Towards this direction, in the present work is presented and evaluated a new modelling approach, based on the combustion rate obtained from the measured cylinder pressure trace using Heat Release Rate Analysis. The model used is a semi-empirical two-zone one which makes use of the estimated elementary fuel mass burnt at each crank angle interval. The combustion process is considered to be adiabatic, while chemical dissociation is also considered. With this approach, temperature distribution throughout the combustion chamber is considered for, together with its evolution during the engine cycle. In addition, O2 availability is also considered for through the calculated charge composition. The result is an extremely fast computational model, combining the advantages of both empirical and physically based ones. In the present work is given a detailed validation of the model, from its application on two different types of diesel engines: a heavy-duty DI diesel engine and a light-duty DI diesel engine with pilot fuel injection. A significant number of cases where tested for both engine configurations, considering different operation points and variation of operating parameters, such as rail pressure and EGR. The twelve points of the European Stationary Cycle (ESC) were covered for the case of the heavy duty DI diesel engine, whilst for the light-duty DI engine a total number of forty-six operating points was studied. For both engine configurations the model reveals a very good predictive ability, considering for the effect of all operating parameters examined on NOx emissions. However, there is potential for improvement and development on its physical base for even more accurate predictions. The merits of good accuracy in prediction trends with varying engine operating parameters — even without calibration — and low computational time establish a potential for model use in engine development, optimization studies and model based control applications.
