A novel cost-effective robust approach for selective catalytic reduction state estimations using dual nitrogen oxide sensors

Abstract

Urea-based selective catalytic reduction systems have become a promising technique in controlling nitrogen oxide emissions from diesel engines in the past decade. One of the continuing issues is the cross-sensitivity characteristics of the current nitrogen oxide sensors to ammonia in the exhaust, which makes nitrogen oxide sensor readings inaccurate in the presence of ammonia. Although prototype ammonia sensors for mobile selective catalytic reduction applications have been introduced for diesel emission control in the past few years, ammonia sensors are still too expensive to be available for mass-produced diesel engines and selective catalytic reduction systems. In order to address these issues, in this paper, a novel, cost-effective, and robust approach is proposed for estimating the key selective catalytic reduction states including the nitric oxide concentration, the nitrogen dioxide concentration, the ammonia concentration, and the ammonia surface coverage ratio, by utilizing two post-selective-catalytic-reduction nitrogen oxide sensors with different ammonia cross-sensitivity factors. Experimental verification results show that the proposed approach has the potential for precisely estimating the four selective catalytic reduction states. Such a novel approach can be instrumental in reducing the cost of selective catalytic reduction diagnosis, selective catalytic reduction estimation, and advanced selective catalytic reduction controls.