Real-Time Simulation of CNG Engine and After-Treatment System Cold Start. Part 2: Tail-Pipe Emissions Prediction Using a Detailed Chemistry Based MOC Model 2023-01-0364

In contrast to the currently primarily used liquid fuels (diesel and gasoline), methane (CH₄) as a fuel offers a high potential for a significant reduction of greenhouse gas emissions (GHG). This advantage can only be used if tailpipe CH₄ emissions are reduced to a minimum, since the GHG impact of CH₄ in the atmosphere is higher than that of carbon dioxide (CO₂). Three-way catalysts (TWC - stoichiometric combustion) and methane oxidation catalysts (MOC - lean combustion) can be used for post-engine CH₄ oxidation. Both technologies allow for a nearly complete CH₄ conversion to CO₂ and water at sufficiently high exhaust temperatures (above the light-off temperature of the catalysts). However, CH₄ combustion is facing a huge challenge with the planned introduction of Euro VII emissions standard, where stricter CH₄ emission limits and a decrease of the cold start starting temperatures are discussed.

The aim of the present study is to develop a reliable kinetic catalyst model for MOC conversion prediction in order to optimize the catalyst design in function of engine operation conditions, by combining the outputs from the predicted transient engine simulations as inputs to the catalyst model. Model development and training has been performed using experimental engine test bench data at stoichiometric conditions as well as engine simulation data and is able to reliably predict the major emissions under a broad range of operating conditions. Cold start (-7°C and +20°C) experiments were performed for a simplified worldwide light vehicle test procedure (WLTP) driving cycle using a prototype gas engine together with a MOC. For the catalyst simulations, a 1-D catalytic converter model was used. The model includes detailed gas and surface chemistry that are computed together with catalyst heat up. In a further step, a virtual transient engine cold start cycle is combined with the MOC model to predict tail-pipe emissions at transient operating conditions. This method allows to perform detailed emission investigations in an early stage of engine prototype development.