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Institute
During cold start of natural gas engines, increased methane and formaldehyde emissions can be released due to flame quenching on cold cylinder walls, misfiring and the catalyst not being fully active at low temperatures. Euro 6 legislation does not regulate methane and formaldehyde emissions. New limits for these two pollutants have been proposed by CLOVE consortium for Euro 7 scenarios. These proposals indicate tougher requirements for aftertreatment systems of natural gas engines.
In the present study, a zero-dimensional model for real-time engine-out emission prediction for transient engine cold start is presented. The model incorporates the stochastic reactor model for spark ignition engines and tabulated chemistry. The tabulated chemistry approach allows to account for the physical and chemical properties of natural gas fuels in detail by using a-priori generated laminar flame speed and combustion chemistry look-up tables. The turbulence-chemistry interaction within the combustion chamber is predicted using a K-k turbulence model. The optimum turbulence model parameters are trained by matching the experimental cylinder pressure and engine-out emissions of nine steady-state operating points.
Subsequently, the trained engine model is applied for predicting engine-out emissions of a WLTP passenger car engine cold start. The predicted engine-out emissions comprise nitrogen oxide, carbon monoxide, carbon dioxide, unburnt methane, formaldehyde, and hydrogen. The simulation results are validated by comparing to transient engine measurements at different ambient temperatures (-7°C, 0°C, 8°C and 20°C). Additionally, the sensitivity of engine-out emissions towards air-fuel-ratio (λ=1.0 and λ=1.3) and natural gas quality (H-Gas and L-Gas) is investigated.
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.
In more or less all aspects of life and in all sectors, there is a generalized global demand to reduce greenhouse gas (GHG) emissions, leading to the tightening and expansion of existing emissions regulations. Currently, non-road engines manufacturers are facing updates such as, among others, US Tier 5 (2028), European Stage V (2019/2020), and China Non-Road Stage IV (in phases between 2023 and 2026). For on-road applications, updates of Euro VII (2025), China VI (2021), and California Low NOx Program (2024) are planned. These new laws demand significant reductions in nitrogen oxides (NOx) and particulate matter (PM) emissions from heavy-duty vehicles. When equipped with an appropriate exhaust aftertreatment system, natural gas engines are a promising technology to meet the new emission standards. Gas engines require an appropriate aftertreatment technology to mitigate additional GHG releases as natural gas engines have challenges with methane (CH4) emissions that have 28 times more global warming potential compared to CO2. Under stoichiometric conditions a three-way catalytic converter (TWC - stoichiometric combustion) can be used to effectively reduce emissions of harmful pollutants such as nitrogen oxides and carbon monoxide (CO) as well as GHG like methane. The aim of the present study is to understand the performance of the catalytic converter in function of the engine operation and coolant temperature in order to optimize the catalyst operating conditions. Different cooling temperatures are chosen as the initial device temperature highly affects the level of warm up emissions such that low coolant temperatures entail high emissions. In order to investigate the catalyst performance, experimental and virtual transient engine emissions are coupled with a TWC model to predict tail-pipe emissions at transient operating conditions. Engine experiments are conducted at two initial engine coolant temperatures (10°C and 25°C) to study the effects on the Non-Road Transient Cycle (NRTC) emissions. Engine simulations of combustion and emissions with acceptable accuracy and with low computational effort are developed using the Stochastic Reactor Model (SRM). Catalyst simulations are performed using a 1D catalytic converter model including detailed gas and surface chemistry. The initial section covers essential aspects including the engine setup, definition of the engine test cycle, and the TWC properties and setup. Subsequently, the study introduces the transient SI-SRM, 1D catalyst model, and kinetic model for the TWC. The TWC model is used for the validation of a NRTC at different coolant temperatures (10°C and 25°C) during engine start. Moving forward, the next section includes the coupling of the TWC model with measured engine emissions. Finally, a virtual engine parameter variation has been performed and coupled with TWC simulations to investigate the performance of the engine beyond the experimental campaign. Various engine operating conditions (lambda variation for this paper) are virtually investigated, and the performance of the engine can be extrapolated. The presented virtual development approach allows comprehensive emission evaluations during the initial stages of engine prototype development
Worldwide, there is the demand to reduce harmful emissions from non-road vehicles to fulfill European Stage V+ and VI (2022, 2024) emission legislation. The rules require significant reductions in nitrogen oxides (NOx), methane (CH4) and formaldehyde (CH2O) emissions from non-road vehicles. Compressed natural gas (CNG) engines with appropriate exhaust aftertreatment systems such as threeway catalytic converter (TWC) can meet these regulations. An issue remains for reducing emissions during the engine cold start where the CNG engine and TWC yet do not reach their optimum operating conditions. The resulting complexity of engine and catalyst calibration can be efficiently supported by numerical models. Hence, it is required to develop accurate simulation models which can predict cold start emissions.
This work presents a real-time engine model for transient engine-out emission prediction using tabulated chemistry for CNG. The engine model is based on a stochastic reactor model (SRM) which describes the in-cylinder processes of spark ignition (SI) engines including large-scale and lowscale turbulence, convective heat transfer, turbulent flame propagation and chemistry. Chemistry is described using a tabulated chemistry model which calculates the major exhaust gas emissions of CNG engines such as CO2, NOx, CO, CH4 and CH2O.
By best practice, the engine model parameters are optimized by matching the experimental cylinder pressure and engine-out emissions from steady-state operating points. The engine model is trained for a non-road transient cycle (NRTC) cold start at 25°C ambient temperature and validated for a NRTC cold start at 10°C ambient temperature. The trained model is evaluated regarding their feasibility and accuracy predicting transient engineout emissions.
Chemical insights into the larger sooting tendency of 2-methyl-2-butene compared to n-pentane
(2019)
A comprehensive, chemically detailed mechanism for the combustion of 2-methyl-2-butene and n-pentane is presented to provide insights into the different sooting tendencies of these two structurally different C5 hydrocarbons. A hierarchically assembled mechanism has been developed to specifically target speciation data from low-pressure premixed flames of 2-methyl-2-butene [Ruwe et al., Combust. Flame, 175, 34-46, 2017] and newly measured mole fraction data for a fuel-rich (ɸ=1.8) n-pentane flame, in which species profiles up to phenol were quantified. The partially isomer-resolved chemical composition of this flame was determined using flame-sampling molecular-beam mass spectrometry with single-photon ionization by tunable, synchrotron-generated vacuum-ultraviolet radiation. The presented model, which includes a newly determined, consistent set of the thermochemistry data for the C5 species, presents overall satisfactory capabilities to predict the mole fraction profiles of common combustion intermediates. The analysis of the model predictions revealed the fuel-structure dependencies (i.e. saturated vs. unsaturated and linear vs. branched) of the formation of small aromatic species that are considered as soot precursors. The propensity of the 2-methyl-2-butene flame to form larger concentrations of aromatic species was traced back to the readily available formation routes of several small precursor molecules and the efficient formation of “first aromatic rings” beyond benzene.