Multi-objective Optimization of Gasoline, Ethanol, and Methanol in Spark Ignition Engines
Tim Franken, Lars Seidel, LC Gonzalez Mestre, KP Shrestha, Fabian Mauß
First published: March 2019
Abstract
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, ethanol, and methanol 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 and Yaws database. 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, which assigns two dimensionless parameters (ξ and ε). 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. 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.