Evaluation of a semi-physical model to predict NOx and soot emissions of a CI automotive engine under warm-up like conditions

Abstract

Due to the short duration of many travels, automotive engines run quite often without having reached their nominal temperature. This greatly influences fuel consumption and tail-pipe emissions and motivates smart engine thermal management. In this context, the engine calibration process becomes more and more challenging and the use of accurate simulation tools can be helpful. Although many experimental studies deal with engine warm-up in the literature, existing 0D/1D models aiming at predicting pollutant emission from Diesel engines are rarely tested under these conditions.In this paper specific experimental tests are first conducted on engine test-bench to evaluate oil and coolant temperatures’ influence on combustion and pollutant emissions.A novel 0D semi-physical model to assess engine-out NOx and soot emissions is then presented. The temperatures of combustion chamber wall (cylinder head, liner and piston head) are estimated as a function of engine speed and load and coolant and oil temperatures, derived from experiments from the literature. Heat losses are then calculated with Hoenberg model, while Barba model is used for heat release rate (HRR). Adiabatic flame temperature is also evaluated, with a two zone approach. Emissions are not calculated on a crank-angle basis but only at exhaust valve opening (EVO), thus saving calculation time. Semi-physical sub-models are used, with the main physical parameters influencing pollutant formation evaluated by the high-frequency 0D model as inputs. The model calibration relies on standard steady state operating points (OP). The model is then tested on another group of OP and shows a good agreement with measurements.Finally, the model capabilities are tested on four OP under warm-up like conditions, with reduced coolant and/or oil temperatures. The main effects of these temperatures on HRR and emissions are correctly predicted by the model. The various evolutions, some of which depend on OP, are analysed and commented.