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Optimization of catalytic converter related to flow improvements, cost and conversion of pollutants using computational model and computational fluid dynamics (CFD) are described in this paper. A computational model is developed for predicting the performance of Pd/Rh catalytic converter at wide range of operating conditions. An experimental investigation was done on Pd/Rh catalytic converter for validating the model. Optimization of the catalytic converter was carried out based on three parameters namely catalytic converter length, cell densities and typical metal loading. The cell densities varied from 200 cpi to 1200 cpi. The length of the catalytic converter varied from 70 mm to 180 mm. About 8 patterns were studied on Pd/Rh catalytic converter. The predicted patterns show that about 48 percent precious metal can be saved by proposed metal loading patterns.

The investigations relating to the evaluation of an automobile catalytic converter are reported in this paper. These investigations are aimed at arriving at a data that would pave the way for the optimization of a catalytic converter by experimental and computer simulation at steady and transient operating conditions The converter used in the present study contains Pd, Rh binary catalyst (10:1) impregnated on ultra thin ceramic substrate. Characterization of catalytic converter was done for its compositions using Inductively Coupled Argon Plasma (ICAP) and Scanning Electron Microscope (SEM). The necessary instrumentation developed, which include pre and post converter emissions, backpressure and exhaust gas temperature are described for both steady and transient conditions. The experimental setup has been designed for assessing the performance of a catalytic converter on a passenger car at different operating conditions.

The objective of this paper is the prediction of efficiency and NOx emission of a Spark Ignition engine based on engine design and operational parameters using artificial neural networks (ANN). This paper deals with quasi-dimensional, two-zone thermodynamic simulation of four-stroke SI engine fueled with biogas. The developed computer model has been used for the prediction of the combustion and emission characteristics of biogas in SI engines. Predicted results indicate that the presence of carbon dioxide can reduce oxides of nitrogen (NOx) emissions, but since lower cylinder pressures result, engine power and thermal efficiency are reduced. This is mainly due to the lower heating value of biogas. Using the results from this program, the effects of operational and design parameters of the engine were investigated. For real time computations in electronic control unit (ECU) an artificial neural network (ANN) model has been suggested as an alternative to the engine simulation model.