@misc{FrankenNetzerMaussetal., author = {Franken, Tim and Netzer, Corinna and Mauß, Fabian and Pasternak, Michal and Seidel, Lars and Borg, Anders and Lehtiniemi, Harry and Matrisciano, Andrea and Kulzer, Andr{\´e} Casal}, title = {Multi-objective optimization of water injection in spark-ignition engines using the stochastic reactor model with tabulated chemistry}, series = {International Journal of Engine Research}, volume = {20}, journal = {International Journal of Engine Research}, number = {10}, issn = {2041-3149}, doi = {10.1177/1468087419857602}, pages = {1089 -- 1100}, abstract = {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.}, language = {en} } @misc{FrankenMaussSeideletal., author = {Franken, Tim and Mauß, Fabian and Seidel, Lars and Gern, Maike Sophie and Kauf, Malte and Matrisciano, Andrea and Kulzer, Andre Casal}, title = {Gasoline engine performance simulation of water injection and low-pressure exhaust gas recirculation using tabulated chemistry}, series = {International Journal of Engine Research}, volume = {21}, journal = {International Journal of Engine Research}, number = {10}, issn = {2041-3149}, doi = {10.1177/1468087420933124}, pages = {1857 -- 1877}, abstract = {This work presents the assessment of direct water injection in spark-ignition engines using single cylinder experiments and tabulated chemistry-based simulations. In addition, direct water injection is compared with cooled low-pressure exhaust gas recirculation at full load operation. The analysis of the two knock suppressing and exhaust gas cooling methods is performed using the quasi-dimensional stochastic reactor model with a novel dual fuel tabulated chemistry model. To evaluate the characteristics of the autoignition in the end gas, the detonation diagram developed by Bradley and coworkers is applied. The single cylinder experiments with direct water injection outline the decreasing carbon monoxide emissions with increasing water content, while the nitrogen oxide emissions indicate only a minor decrease. The simulation results show that the engine can be operated at l = 1 at full load using water-fuel ratios of up to 60\% or cooled low-pressure exhaust gas recirculation rates of up to 30\%. Both technologies enable the reduction of the knock probability and the decrease in the catalyst inlet temperature to protect the aftertreatment system components. The strongest exhaust temperature reduction is found with cooled low-pressure exhaust gas recirculation. With stoichiometric air-fuel ratio and water injection, the indicated efficiency is improved to 40\% and the carbon monoxide emissions are reduced. The nitrogen oxide concentrations are increased compared to the fuel-rich base operating conditions and the nitrogen oxide emissions decrease with higher water content. With stoichiometric air-fuel ratio and exhaust gas recirculation, the indicated efficiency is improved to 43\% and the carbon monoxide emissions are decreased. Increasing the exhaust gas recirculation rate to 30\% drops the nitrogen oxide emissions below the concentrations of the fuel-rich base operating conditions.}, language = {en} } @misc{FrankenSrivastavaLeeetal., author = {Franken, Tim and Srivastava, Vivek and Lee, Sung-Yong and Heuser, Benedikt and Shrestha, Krishna Prasad and Seidel, Lars and Mauß, Fabian}, title = {Numerical Analysis of the Combustion of Diesel, Dimethyl Ether, and Polyoxymethylene Dimethyl Ethers (OMEn, n=1-3) Using Detailed Chemistry}, series = {THIESEL 2022 : Conference on Thermo- and Fluid-Dynamics of Clean Propulsion Powerplants, 13th-16th September 2022 : conference proceedings}, journal = {THIESEL 2022 : Conference on Thermo- and Fluid-Dynamics of Clean Propulsion Powerplants, 13th-16th September 2022 : conference proceedings}, editor = {Xandra, Margot and Payri, Ra{\´u}l and Serrano, Jos{\´e} Ram{\´o}n}, publisher = {Editorial Universitat Polit{\`e}cnica de Val{\`e}ncia}, address = {Val{\`e}ncia}, isbn = {978-84-1396-055-5}, doi = {10.4995/Thiesel.2022.632801}, abstract = {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.}, language = {en} } @misc{SiddareddyFrankenPasternaketal., author = {Siddareddy, Reddy Babu and Franken, Tim and Pasternak, Michal and Leon de Syniawa, Larisa and Oder, Johannes and Rottengruber, Hermann and Mauß, Fabian}, title = {Real-Time Simulation of CNG Engine and After-Treatment System Cold Start. Part 1: Transient Engine-Out Emission Prediction Using a Stochastic Reactor Model}, series = {SAE Technical Paper}, journal = {SAE Technical Paper}, issn = {2688-3627}, doi = {10.4271/2023-01-0183}, abstract = {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.}, language = {en} }