We present herein the final part in the development and validation of a two-site kinetic model for NH3-SCR over Cu-SSZ-13. To predict tailpipe emissions accurately, it was necessary to combine the kinetic model of the SCR catalyst developed in part I (Daya et al. 2018), with a reaction-diffusion model of the dual-layer ammonia slip catalyst (ASC). This dual-layer ASC model was developed following a three-step process, including development of the kinetic models of the individual layers, followed by parameterization of a parallel pore diffusion model of the dual-layer ASC. Reactor-scale validation of the dual-layer ASC model confirmed the kinetic model accuracy and highlighted the significance of intra-porous diffusion. Following this, the SCR model developed in part I of this paper was validated on an engine dynamometer through comprehensive steady-state experiments with inlet NH3 to NOx ratio (ANR) sweeps. The final SCR and ASC models were then evaluated on cold and hot heavy-duty transient (HDT) cycles, to examine the capability of predicting tailpipe NOx, NH3 slip as well as storage-based dynamics. Overall cycle-averaged NOx conversion was predicted within 3% using these models. Validated models have significant application in model-based control as well as improving catalyst design through improved functional understanding. The present Cu-SSZ-13 SCR model was simulated using the four-step SCR protocol (Kamasamudram et al. Catal. Today 151(3):212–222) to calculate the intra-catalyst dynamic capacity. These numerical experiments showed that the dynamic capacity decreases upon hydrothermal aging but leads to higher NOx conversion under standard and fast SCR conditions at 250 °C. This increase in NOx conversion is due to more uniform NH3 storage along the length of the catalyst, leading to higher NH3 utilization near the rear of the aged catalyst. Similar numerical experiments on the dual-layer ASC model demonstrated intra-layer washcoat distributions causing NO slip during transient drive cycles for both hydrothermal aging conditions.
Read full abstract