Computational Methodology for Knocking Combustion Analysis in Compression-Ignited Advanced Concepts

Abstract

In the present work, a numerical methodology based on three-dimensional (3D) computational fluid dynamics (CFD) was developed to predict knock in a 2-Stroke engine operating with gasoline Partially Premixed Combustion (PPC) concept. Single-cycle Unsteady Reynolds-Averaged Navier Stokes (URANS) simulations using the renormalization group (RNG) k − ε model were performed in parallel while the initial conditions are accordingly perturbed in order to imitate the variability in the in-cylinder conditions due to engine operation. Results showed a good agreement between experiment and CFD simulation with respect to cycle-averaged and deviation of the ignition timing, combustion phasing, peak pressure magnitude and location. Moreover, the numerical method was also demonstrated to be capable of predicting knock features, such as maximum pressure rise rate and knock intensity, with good accuracy. Finally, the CFD solution allowed to give more insight about in-cylinder processes that lead to the knocking combustion and its subsequent effects.In particular, PPC operated with low reacting fuels, such as gasoline, have shown encouraging results to achieve very low pollutant emissions while maintaining, or even improving, the thermal efficiency [10][11][12]. Indeed, this combustion concept operated in an innovative 2-Stroke high speed direct injection (HSDI) compression-ignited (CI) engine [13] offers a good flexibility to control the combustion timing and to extent the load range [14][15][16].This concept operates between completely premixed and fully diffusive conditions, whereby low pollutant emissions may be attained. However, to achieve these conditions while retaining an accurate combustion timing control with the injection event remains as the main drawback of this particular system when operating under transient conditions.Despite the attractive benefits of this engine system, its complexity due to the large number of parameters to be managed requires the use of optimization techniques which ensure greater flexibility, speed and lower costs than purely experimental procedures.In this framework, the use of computational fluid dynamics (CFD) simulations is nowadays widely established in both the research community and the automotive industry. Here, aspects such as the simulation of turbulence and how it couples with the chemistry [17] are still the main limiting factors for reproducing the reacting flow field accurately. Since the requirements in both fields tend to differ, specially in terms of time available, the approaches used are also usually different. While in the industry sector, simulations are based on Unsteady Reynolds-averaged Navier-Stokes (URANS) turbulence modelling [18,19] and flamelet-based combustion models [20] owing its lower computational demands, the research community prefer to resort to high-fidelity combustion models and more complex turbulence schemes such as Large Eddy Simulations (LES) [21] or Direct Numerical Simulations (DNS) [22].Although the industry standard tends to simplify the simulatio...

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