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1 Nowadays, In-Cylinder Pressure Sensors (ICPS) have become a mainstream technology that promises to change the way the engine control is performed. Among all the possible applications, the prediction of raw (engine-out) NOX emissions would allow to eliminate the NOX sensor currently used to manage the after-treatment systems. In the current study, a semi-physical model already existing in literature for the prediction of engine-out nitric oxide emissions based on in-cylinder pressure measurement has been improved; in particular, the main focus has been to improve nitric oxide prediction accuracy when injection timing is varied. The main modification introduced in the model lies in taking into account the turbulence induced by fuel spray and enhanced by in-cylinder bulk motion.

The incoming RDE regulation and the on-board diagnostics -OBD- pushes the research activity towards the set-up of a more and more efficient after treatment system. Nowadays, the most common after treatment system for NOx reduction is the selective catalytic reduction -SCR- . This system requires as an input the value of engine out NOx emission -raw- in order to control the Urea dosing strategy. In this work, an already existing grey box NOx raw emission model based on in-cylinder pressure signal (ICPS) is validated on two standard cycles: MNEDC and WLTC using an EU6 engine at the test bench. The overall results show a maximum relative error of the integrated cumulative value of 12.8% and 17.4% for MNEDC and WLTC respectively. In particular, the instantaneous value of relative error is included in the range of ± 10% in the steady state conditions while during transient conditions is less than 20% mainly.