Selective Catalytic Reduction is a key technology, used for NOx abatement. There are several models available for SCR system performance out of which most are experimentally verified only in flow reactors with simulated gaseous concentration and standard test conditions. But in the vehicle as well as in the engine test bench the conditions are very much dynamic compared to the simulated conditions of the lab. This transient behaviour emphasizes the need for a best fit model which accommodates the real-world dynamic conditions, thus reducing the overall effort in SCR catalyst selection for any given engine or vehicle application. The primary objective of this paper is to derive an empirical and mathematical efficiency model for SCR catalyst performance through a model-based design approach. The output from the model is compared with the experimental results from the vehicle and engine test bench, to validate the model accuracy. The model is a function of system specific parameters like space velocity, NO2 ratio, system efficiency, catalyst loading and ageing factors, temperature mapping, for various engine operating zones that are benchmarked from existing experimental results and chemical kinetics that are already incorporated in existing models. This model is fine-tuned by incorporating experimental data and simulated with different control strategies to further refine and optimize the catalyst performance and reduce DEF consumption and ammonia slip formation. The model output from numerical simulations and experimental results are used to derive the control strategy for the best overall efficiency model.
