A Review of the Literature on Modelling of Integrated SCR-in-DPF Systems



WCX™ 17: SAE World Congress Experience
Authors Abstract
The integration of selective catalytic reduction catalysts (SCR) into diesel particulate filters (DPF) as a way to treat nitrogen oxides (NOx) and particulate matter (PM) emission is an emerging technology in diesel exhaust aftertreatment. This is driven by ever-tightening limits on NOx and PM emission. In an integrated SCR-in-DPF (also known as SCRF®, SCR-on-DPF, SDPF, or SCR coated filter), the SCR catalyst is impregnated within the porous walls of the DPF. The compact, low weight/volume of the integrated unit provides improvement in the diesel engine cold start emission performance. Experimental investigations have shown comparable performance with standard SCR and DPF units for NOx conversion and PM control, respectively. The modelling of the integrated unit is complicated. The main challenge is how to best capture the complexity of the physical phenomena-e.g., the competition of soot oxidation and SCR reaction for available NO2, or the interaction of washcoat loading on deNOx performance, PM filtration efficiency and system pressure drop-in a simplified but adequate representation. This paper reviews the approaches to SCR-in-DPF modelling obtained from published materials. It discusses the specific considerations given to adapting coated (catalysed) DPF model for SCR-in-DPF modelling. This includes characterisation of SCR model and associated kinetics, inclusion of ammonia dynamics and interaction with soot in the transport model, and careful model calibration to capture the salient phenomena in the system. This work presents current research in SCR-in-DPF modelling and highlights potential areas of future research. It can serve as a resource for new researchers in SCR-in-DPF modelling
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Olowojebutu, S., and Steffen, T., "A Review of the Literature on Modelling of Integrated SCR-in-DPF Systems," SAE Technical Paper 2017-01-0976, 2017, https://doi.org/10.4271/2017-01-0976.
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Mar 28, 2017
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Technical Paper