Title :
Model-based estimation of injected urea quantity and diagnostics for SCR urea injection system
Author :
Yue-Yun Wang ; Yu Sun ; Gady, K.
Author_Institution :
Propulsion Syst. Res. Lab., GM R&D, Warren, MI, USA
Abstract :
Urea injection system is one of the key devices for urea-SCR after treatment technology, since accurate injection determines vehicle exhaust NOx reduction performance. This paper proposes a new diagnostic approach for an SCR urea injection system through the model based estimation of the injected urea mass flow without costing a urea flow sensor. The estimation is based on a urea pump physical model, which is identified by using system identification technique with the existing production sensors as the inputs. Kalman filter is further applied to filter out estimation noises. Injector deterioration is diagnosed by comparing an estimated injected urea quantity to a commanded quantity. The approach has been validated by an onboard rapid prototyping control system. Experimental results have shown the effectiveness of this approach.
Keywords :
Kalman filters; automotive engineering; estimation theory; flow sensors; pollution; road vehicles; Kalman filter; SCR urea injection system diagnostics; estimation noises; injected urea mass flow; injected urea quantity; injector deterioration; model-based estimation; production sensors; rapid prototyping control system; system identification technique; urea flow sensor; urea pump physical model; urea-SCR aftertreatment technology; Equations; Estimation; Mathematical model; Orifices; Predictive models; Pulse width modulation; Thyristors;
Conference_Titel :
American Control Conference (ACC), 2012
Conference_Location :
Montreal, QC
Print_ISBN :
978-1-4577-1095-7
Electronic_ISBN :
0743-1619
DOI :
10.1109/ACC.2012.6314711