The newly introduced Real Driving Emission –RDE - regulation and the mandatory on-board diagnostics pushes the automotive research activity towards the set-up of a more and more efficient emission reduction strategy. In particular, this work deals with NOx reduction in a Diesel engine. Nowadays, the most promising after treatment system for NOx reduction is the one based on selective catalytic reduction (SCR). This system requires as an input the value of engine out NOx emission, also called NOx raw emission, in order to control the urea dosing strategy even when the NOx sensor is not mounted or not activated. In this two particular cases, a raw NOx emission model, implemented in the ECU, substitutes the NOx sensor. Therefore, in the first part of this thesis, an already existing semi-empirical NOx raw emission model based on the in-cylinder pressure signal (ICPS) is improved. It 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 NOx value of 12.8% and 17.4% for MNEDC and WLTC respectively. In particular, the instantaneous value of relative error is within the range of ± 10% in steady state conditions while during transient conditions is mainly less than 20%. The aim of the second part of the activity is the introduction of the complete NOx reduction reaction scheme instead of the unique NOx reduction reaction already implemented in an existing SCR kinetic model developed by Bosch. Due to the non-linearity nature of the problem, an explicit method is not adequate to solve the problem. Therefore, an implicit Runge-Kutta method is implemented. The model is calibrated on a WLTC cycle and on a RDE track with the following results: the maximum relative error of the integrated cumulative NOx value is 2.15% and 10.66% for WLTC and RDE respectively for the improved model version.
|Titolo:||Development of NOx Estimator ECU Models for SCR After Treatment System in a Diesel Engine|
|Data di pubblicazione:||2018|
|Appare nelle tipologie:||5.14 Tesi di dottorato|