TY - GEN A1 - Franken, Tim A1 - Netzer, Corinna A1 - Mauß, Fabian A1 - Pasternak, Michal A1 - Seidel, Lars A1 - Borg, Anders A1 - Lehtiniemi, Harry A1 - Matrisciano, Andrea A1 - Kulzer, André Casal T1 - Multi-objective optimization of water injection in spark-ignition engines using the stochastic reactor model with tabulated chemistry T2 - International Journal of Engine Research N2 - Water injection is investigated for turbocharged spark-ignition engines to reduce knock probability and enable higher engine efficiency. The novel approach of this work is the development of a simulation-based optimization process combining the advantages of detailed chemistry, the stochastic reactor model and genetic optimization to assess water injection. The fast running quasi-dimensional stochastic reactor model with tabulated chemistry accounts for water effects on laminar flame speed and combustion chemistry. The stochastic reactor model is coupled with the Non-dominated Sorting Genetic Algorithm to find an optimum set of operating conditions for high engine efficiency. Subsequently, the feasibility of the simulation-based optimization process is tested for a three-dimensional computational fluid dynamic numerical test case. The newly proposed optimization method predicts a trade-off between fuel efficiency and low knock probability, which highlights the present target conflict for spark-ignition engine development. Overall, the optimization shows that water injection is beneficial to decrease fuel consumption and knock probability at the same time. The application of the fast running quasi-dimensional stochastic reactor model allows to run large optimization problems with low computational costs. The incorporation with the Non-dominated Sorting Genetic Algorithm shows a well performing multi-objective optimization and an optimized set of engine operating parameters with water injection and high compression ratio is found. KW - Water Injection KW - Genetic Optimization KW - Spark Ignition Engine KW - Stochastic Reactor Model KW - Detailed Chemistry Y1 - 2019 UR - https://journals.sagepub.com/doi/full/10.1177/1468087419857602 U6 - https://doi.org/10.1177/1468087419857602 SN - 2041-3149 VL - 20 IS - 10 SP - 1089 EP - 1100 ER - TY - GEN A1 - Franken, Tim A1 - Srivastava, Vivek A1 - Lee, Sung-Yong A1 - Heuser, Benedikt A1 - Shrestha, Krishna Prasad A1 - Seidel, Lars A1 - Mauß, Fabian ED - Xandra, Margot ED - Payri, Raúl ED - Serrano, José Ramón T1 - Numerical Analysis of the Combustion of Diesel, Dimethyl Ether, and Polyoxymethylene Dimethyl Ethers (OMEn, n=1-3) Using Detailed Chemistry T2 - THIESEL 2022 : Conference on Thermo- and Fluid-Dynamics of Clean Propulsion Powerplants, 13th-16th September 2022 : conference proceedings N2 - New types of synthetic fuels are introduced in internal combustion engine applications to achieve carbon-neutral and ultra-low emission combustion. Dimethyl Ether (DME) and Polyoxymethylene Dimethyl Ethers (OMEn) belong to such kind of synthetic fuels. Recently, Shrestha et al. (2022) have developed a novel detailed chemistry model for OMEn (n=1-3) to predict the ignition delay time, laminar flame speed and species formation for various thermodynamic conditions. The detailed chemistry model is applied in the zero dimensional (0D) stochastic reactor model (DI-SRM) to investigate the non-premixed combustion in a 2-liter diesel engine. Further insights in the formation of unburned hydrocarbons (HC), carbon monoxide and nitrogen oxides during the combustion of OMEn fuels are obtained in this work. The combustion and emission formation of DME and OMEn (n=1-3) are investigated and compared to conventional Diesel combustion. The mixture formation is governed by an earlier vaporization of the DME and OMEn fuels, faster homogenization of the respective air-fuel mixture and higher reactivity. At the same injection pressure, the OMEn fuels obtain higher NOx but lower CO and HC emissions. High amounts of aromatics, ethene, methane formaldehyde and formic acid are found within the Diesel exhaust gas. The DME and OMEn exhaust gas contains higher fractions of formaldehyde and formic acid, and fractions of methane, methyl formate and nitromethane. KW - Polyoxymethylene Dimethyl Ethers KW - Stochastic Reactor Model KW - Detailed Chemistry KW - Modelling KW - Emissions Y1 - 2022 UR - https://www.lalibreria.upv.es/portalEd/UpvGEStore/products/p_6328-1-1 SN - 978-84-1396-055-5 U6 - https://doi.org/10.4995/Thiesel.2022.632801 PB - Editorial Universitat Politècnica de València CY - València ER - TY - GEN A1 - Franken, Tim A1 - Shrestha, Krishna Prasad A1 - Seidel, Lars A1 - Mauß, Fabian ED - Sens, Marc T1 - Effect of Gasoline–Ethanol–Water Mixtures on Auto-Ignition in a Spark Ignition Engine T2 - International Conference on Knocking in Gasoline Engines N2 - The climate protection plan of the European Union requires a significant reduction of CO2 emissions from the transportation sector by 2030. Today ethanol is already blended by 10vol-% in gasoline and further increase of the ethanol content to 20vol-% is discussed. During the ethanol production process, distillation and molecular sieving is required to remove the water concentration to achieve high-purity ethanol. However, hydrous ethanol can be beneficial to suppress knock of spark ignition engines. The hygroscopic nature of ethanol can allow to increase the water content in gasoline – water emulsions even more, without adding additional surfactants, and improve the thermal efficiency by optimized combustion phasing, while keeping the system complexity low. Hence, the effect of gasoline – ethanol – water mixtures on the auto-ignition in a single-cylinder spark ignition engine is investigated by using multi-dimensional simulation and detailed chemistry. The gasoline – ethanol mixtures are defined to keep the Research Octane Number constant, while the Motored Octane Number is decreasing. In total five surrogates are defined and investigated: E10 (10vol-% ethanol-in-gasoline), E20, E30, E70 and E100. The water content is determined according to experimentally defined ternary diagrams that evaluated stable gasoline – ethanol – water emulsion at different gasoline – ethanol blending ratios. The auto-ignition modes of the surrogates are analyzed using the diagram, which determines if hotspots are within harmless deflagration or harmful developing detonation regime. The strongest auto-ignition is observed for the E10 surrogate, while increasing ethanol content reduces the surrogate reactivity and increases the resonance parameter. No auto-ignition of the unburnt mixture is observed for the E70 and E100 surrogates. The addition of hydrous ethanol decreased the excitation time of the surrogates, especially at low ethanol content, wherefor the reactivity parameter is significantly increased. The hotspots for E10, E20 and E30 surrogates with hydrous ethanol are found within the developing detonation regime, while hotspots of the E70 surrogate with hydrous ethanol are found in the transition regime. For the hydrous E100 surrogate no auto-ignition is predicted because of reduced temperature of the unburnt mixture due to water vaporization, which outweighs the increased reactivity due to water vapor addition. KW - Knock KW - Gasoline KW - Ethanol KW - Simulation KW - Detailed Chemistry KW - Spark Ignition Y1 - 2022 SN - 978-3-8169-3544-5 U6 - https://doi.org/10.24053/9783816985440 SP - 175 EP - 222 PB - expert CY - Tübingen ER - TY - GEN A1 - Leon de Syniawa, Larisa A1 - Siddareddy, Reddy Babu A1 - Oder, Johannes A1 - Franken, Tim A1 - Günther, Vivien A1 - Rottengruber, Hermann A1 - Mauß, Fabian T1 - 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 T2 - SAE Technical Report N2 - 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. KW - Exhaust Emissions KW - Tail Pipe Emissions KW - Three Way Catalyst KW - Gas Engines KW - Cold Start KW - Simulation KW - Detailed Chemistry KW - Methane Oxidation Catalyst KW - Methane KW - Co-Simulation KW - Catalysts Y1 - 2023 U6 - https://doi.org/10.4271/2023-01-0364 SN - 2688-3627 SN - 0148-7191 ER -