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Selective Catalytic Reduction (SCR) of oxides of nitrogen (NOx) with ammonia gas has established itself as an effective diesel aftertreatment technology to meet stringent emission standards enforced by worldwide regulatory bodies. Typically, in this technology, aqueous urea solution of eutectic composition - known as Diesel Exhaust Fluid (DEF) - is injected into hot exhaust gases leading to a series of thermal, fluid dynamic and reactive processes that eventually produces the ammonia necessary for NOx reduction reactions within monolithic catalytic substrates. Incomplete decomposition of the injected urea can lead to formation of solid deposits that adversely affect system performance by increasing the engine back pressure, reducing de-NOx efficiency, and lowering the overall fuel economy.

U.S. and European nonroad diesel emissions regulations have led to the implementation of various exhaust aftertreatment solutions. One approved configuration, a vanadium-based selective catalytic reduction catalyst followed by an ammonia oxidation catalyst (V-SCR + AMOX), does not require the use of a diesel oxidation catalyst (DOC) or diesel particulate filter (DPF). While certification testing has shown the V-SCR + AMOX system to be capable of meeting the nitrogen oxides, carbon monoxide, and particulate matter requirements, open questions remain regarding the efficacy of this aftertreatment for volatile and nonvolatile organic emissions removal, especially since the removal of this class of compounds is generally attributed to both the DOC and DPF.

SCR on Filter (SCRoF) is an efficient and compact NOX and PM reduction technology already used in series production for light-duty applications. The technology is now finding its way into the medium duty and heavy duty market. One of the key challenges for successful application is the robustness to real world variations. The solution to this challenge can be found by using model-based control algorithms, utilizing state estimation by physics-based catalyst models. This paper focuses on the development, validation and real time implementation of a physics-based control oriented SCRoF model. An overview of the developed model will be presented, together with a brief description of the model parameter identification and validation process using engine test bench measurement data. The model parameters are identified following a streamlined approach, focusing on decoupling the effects of deNOx and soot phenomena.