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 - Mauß, Fabian A1 - Seidel, Lars A1 - Gern, Maike Sophie A1 - Kauf, Malte A1 - Matrisciano, Andrea A1 - Kulzer, Andre Casal T1 - Gasoline engine performance simulation of water injection and low-pressure exhaust gas recirculation using tabulated chemistry T2 - International Journal of Engine Research N2 - 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. KW - Water Injection KW - Exhaust Gas Recirculation KW - Efficiency KW - Spark Ignition Engine KW - Stochastic Reactor Model KW - Emissions Y1 - 2020 UR - https://journals.sagepub.com/doi/abs/10.1177/1468087420933124 U6 - https://doi.org/10.1177/1468087420933124 SN - 2041-3149 SN - 1468-0874 VL - 21 IS - 10 SP - 1857 EP - 1877 ER - TY - GEN A1 - Franken, Tim A1 - Seidel, Lars A1 - Shrestha, Krishna Prasad A1 - Gonzalez Mestre, Laura Catalina A1 - Mauß, Fabian T1 - Multi-objective Optimization of Gasoline, Ethanol, and Methanol in Spark Ignition Engines N2 - In this study, an engine and fuel co-optimization is performed to improve the efficiency and emissions of a spark ignition engine utilizing detailed reaction mechanisms and stochastic combustion modelling. The reaction mechanism for gasoline surrogates (Seidel 2017), ethanol, and methanol (Shrestha et al. 2019) is validated for experiments at different thermodynamic conditions. Liquid thermophysical properties of the RON95E10 surrogate (iso-octane, n-heptane, toluene, and ethanol mixture), ethanol, and methanol are determined using the NIST standard reference database (NIST 2018) and Yaws database (Yaws 2014). The combustion chemistry, laminar flame speed, and thermophysical data are pre-compiled in look-up tables to speed up the simulations (tabulated chemistry). The auto-ignition in the stochastic reactor model is predicted by the detailed chemistry and subsequently evaluated using the Bradley Detonation Diagram (Bradley et al. 2002, Gu et al. 2003, Neter 2019), which assigns two dimensionless parameters (resonance parameter and reactivity parameter). According to the defined developing detonation limits, the auto-ignition is either in deflagration, sub-sonic auto-ignition, or developing detonation mode. Ethanol and methanol show a knock-reducing characteristic, which is mainly due to the high heat of vaporization. The multi-objective optimization process includes mathematical algorithms for design space exploration with Uniform Latin Hypercube, pareto front convergence with Non-dominated Sorting Genetic Algorithm II (NSGA-II), and multi-criteria decision making (Deb et al. 2002). The optimization input parameter ranges are selected according to the previous sensitivity analysis, and the objectives are to minimize specific CO2 and specific CO and maximize indicated efficiency. The performance study of different optimization algorithms shows that the incorporation of metamodels is beneficial to improve the design space exploration, while keeping the optimization duration low. The comparison of different reaction mechanisms, which are applied in the optimization process, shows a strong impact on the pareto front solutions. This is due to differences in the emission formation and auto-ignition between the different reaction schemes. Overall, the engine efficiency is increased by 3.5 % points, and specific CO2 emissions are reduced by 99 g/kWh for ethanol and 142 g/kWh for methanol combustion compared to the base case. This is achieved by advanced spark timing, lean combustion, and reduced C:H ratio of ethanol and methanol in relation to RON95E10. KW - Optimization KW - Methanol KW - Ethanol KW - Spark Ignition Engine KW - Gasoline KW - Simulation Y1 - 2021 UR - https://www.researchgate.net/publication/351688526_Multi-objective_Optimization_of_Gasoline_Ethanol_and_Methanol_in_Spark_Ignition_Engines ER -