Passive Ammonia SCR and Filtration Modeling for Fuel-neutral Engine Aftertreatment Systems

Gong, J. Passive Ammonia SCR and Filtration Modeling for Fuel-Neutral Engine Aftertreatment Systems. University of Wisconsin-Madison, 2014.

Passive ammonia SCR system models including a TWC model and a SCR model are developed. The TWC kinetic model is developed based on the engine dynamometer data collected on a lean burn spark ignition direct injection (SIDI) engine. Ammonia and nitrous oxide formation kinetics are included in the TWC model. A global SCR model including ammonia storage, ammonia oxidation, NO oxidation, three SCR reactions (standard SCR, fast SCR and NO2 SCR) and N2O formation is developed on a Cu-chabazite (CHA) NH3-SCR catalyst. An improve ammonia storage model is developed to model the ammonia storage at different temperatures. Experimental data collected on a flow bench SCR reactor based on a well-designed experimental SCR protocol at Oak Ridge National Lab (ORNL) are used for SCR model calibrations and validations. The TWC and SCR models are found to be able to predict the DeNOx performance over a wide range of engine exhaust conditions.

Motivated by modeling of gasoline particulate filters (GPFs), a PDF based heterogeneous multi-scale filtration (HMF) model is developed to calculate filtration efficiency of particulate filters. The HMF model overcomes the limitations of classic mean filtration models which rely on tuning of the mean collector size. The HMF model is validated on various scales of filter samples and is found to give better predictions of filtration efficiencies compared to the mean filtration model. A dynamic version of HMF model is developed as well to study the dynamic filtration process. Filtration experimental data from exhaust filtration analysis (EFA) system are used for model validations. The dynamic HMF model is found to be able to capture the dynamic filtration process. Finally, filtration characteristics of fuel neutral particulates are studied by using the dynamic HMF model. Particulate penetration length is found to be influenced by the interactions between the filter and particulates. The change of the filter structure and the shape of the particulate size distribution play important role on particulate filtration. It is found that the HMF model is a useful diagnostic tool for filtration investigation.