Ammonia Slip Estimation Based on ASC Control-Oriented Modelling And OBD NOx Sensor Cross-Sensitivity Analysis

Abstract

Abstract The incoming emission regulations for internal combustion engines are gradually introducing new pollutant species, which requires greater complexity of the exhaust gas aftertreatment systems concerning layout, control and diagnostics. This is the case of ammonia, which is already regulated in heavy-duty vehicles and to be included in the emissions standards applied to passenger cars. The ammonia is injected into the exhaust gas through urea injections for NOx abatement in selective catalytic reduction (SCR) systems and can be also generated in other aftertreatment systems as three-way catalysts. However, ammonia slip may require removal on a dedicated catalyst called ammonia slip catalyst (ASC). The set consisting of the urea injection system, SCR and ASC requires control and on-board diagnostic tools to ensure high NOx conversion efficiency and minimization of the ammonia slip under real driving conditions. These tasks are based on the use of NOx sensors ZrO2 pumping cell-based, which present as a drawback high cross-sensitivity to ammonia. Consequently, the presence of this species can affect the measurement of NOx and compromise SCR-ASC control strategies. In the present work, a methodology to predict ammonia and NOx tailpipe emissions is proposed. For this purpose, a control-oriented ASC model was developed to use its ammonia slip prediction to determine the cross-sensitivity correction of the NOx sensor placed downstream of the ASC. The model is based on a simplified solution of the transport equations of the species involved in the main ASC reactions. The ammonia slip model was calibrated using steady- and quasi-steady-state tests performed in a Euro 6c diesel engine. Finally, the performance of the proposed methodology to predict NOx and ammonia emissions was evaluated against experimental data corresponding to Worldwide harmonized Light vehicles Test Cycles (WLTC) applying different urea dosing strategies.