Cycle-to-cycle variations are important to consider in the development of spark-ignition engines to further increase fuel conversion efficiency. Direct numerical simulation and large eddy simulation can predict the stochastics of flows and therefore cycle-to-cycle variations. However, the computational costs are too high for engineering purposes if detailed chemistry is applied. Detailed chemistry can predict the fuels’ tendency to auto-ignite for different octane ratings as well as locally changing thermodynamic and chemical conditions which is a prerequisite for the analysis of knocking combustion. In this work, the joint use of unsteady Reynolds-averaged Navier–Stokes simulations for the analysis of the average engine cycle and the spark-ignition stochastic reactor model for the analysis of cycle-to-cycle variations is proposed. Thanks to the stochastic approach for the modeling of mixing and heat transfer, the spark-ignition stochastic reactor model can mimic the randomness of turbulent flows that is missing in the Reynolds-averaged Navier–Stokes modeling framework. The capability to predict cycle-to-cycle variations by the spark-ignition stochastic reactor model is extended by imposing two probability density functions. The probability density function for the scalar mixing time constant introduces a variation in the turbulent mixing time that is extracted from the unsteady Reynolds-averaged Navier–Stokes simulations and leads to variations in the overall mixing process. The probability density function for the inflammation time accounts for the delay or advancement of the early flame development. The combination of unsteady Reynolds-averaged Navier–Stokes and spark-ignition stochastic reactor model enables one to predict cycle-to-cycle variations using detailed chemistry in a fraction of computational time needed for a single large eddy simulation cycle.
Following the resonance theory by Bradley and co-workers, engine knock is a consequence of an auto-ignition in the developing detonation regime. Their detonation diagram was developed using direct numerical simulations and was applied in the literature to engine knock assessment using large eddy simulations. In this work, it is analyzed if the detonation diagram can be applied for post-processing and evaluation of predicted auto-ignitions in Reynolds-averaged Navier–Stokes simulations even though the Reynolds-averaged Navier–Stokes approach cannot resolve the fine structures resolved in direct numerical simulations and large eddy simulations that lead to the prediction of a developing detonation. For this purpose, an engine operating point at the knock limit spark advance is simulated using Reynolds-averaged Navier–Stokes and large eddy simulations. The combustion is predicted using the G-equation and the well-stirred reactor model in the unburnt gases based on a detailed gasoline surrogate reaction scheme. All the predicted ignition kernels are evaluated using the resonance theory in a post-processing step. According to the different turbulence models, the predicted pressure rise rates and gradients differ. However, the predicted ignition kernel sizes and imposed gas velocities by the auto-ignition event are similar, which suggests that the auto-ignitions predicted by Reynolds-averaged Navier–Stokes simulations can be given a meaningful interpretation within the detonation diagram.
Impact of the surrogate formulation on 3D CFD engine knock prediction using detailed chemistry
(2019)
For engine knock prediction, surrogate fuels are often composed of iso-octane and n-heptane since they are the components of the Primary Reference Fuel (PRF). By definition, a PRF has no octane sensitivity (S = RON-MON). However, for a commercial gasoline fuel holds RON > MON and therefor S > 0. More complex surrogates are Toluene Reference Fuels (TRF) and Ethanol containing Toluene Reference Fuels (ETRF). In this work, the impact of the surrogate formulation on the prediction of flame propagation and auto-ignition in the unburnt gases are investigated. The surrogates are composed such that the Research Octane Number is the same. The auto-ignition events ahead of the flame front are predicted using 3D CFD and a combustion model based on the ETRF mechanism by Seidel (2017). The strength of the auto-ignition is determined using the detonation diagram by Bradley and co-workers (2002, 2003). Applying the different surrogates, ignition kernels of different size and reactivity are predicted. The results indicate a dependency on the local temperature history and the low temperature chemistry of the fuel species. The comparison of homogenous constant volume reactor and transient simulations show that the analysis of ignition delay time and octane rating solely from homogenous simulations is not sufficient if the knock tendency of a surrogate in engine simulations needs to be characterized.
Engine knock is an important phenomenon that needs consideration in the development of gasoline-fueled engines. In our days, this development is supported using numerical simulation tools to further understand and predict in-cylinder processes. In this work, a model tool chain which uses a detailed chemical reaction scheme is proposed to predict the auto-ignition behavior of fuels with different octane ratings and to evaluate the transition from harmless auto-ignitive deflagration to knocking combustion. In our method, the auto-ignition characteristics and the emissions are calculated using a gasoline surrogate reaction scheme containing pathways for oxidation of ethanol, toluene, n-heptane, iso-octane and their mixtures. The combustion is predicted using a combination of the G-equation based flame propagation model utilizing tabulated laminar flame speeds and well-stirred reactors in the burned and …