An adaptive multi-grid chemistry (AMC) model for efficient simulation of HCCI and DI engine combustion

Abstract

There is a need to reduce the computational expense of practical multidimensional combustion simulations. Simulation of Homogeneous Charge Compression Ignition (HCCI) engine processes requires consideration of detailed chemistry in order to capture the ignition and combustion characteristics. Even with relatively coarse numerical meshes and reduced chemistry mechanisms, calculation times are still unacceptably long. For the simulation of Direct Injection (DI) engines, fine meshes are needed to achieve the resolution required by the spray and mixing models, and they are computationally expensive even with reduced chemistry. In addition, the increasing application of CFD for engine design optimization is pushing the demand to reduce computational time. In current design optimizations, depending on the size of the parametric space, hundreds of individual simulations are needed. This work presents an efficient Adaptive Multi-grid Chemistry (AMC) model that can be used in engine CFD codes for simulations of HCCI and DI engines with detailed chemistry. It was found that the number of cells computed with the chemistry solver can be reduced by two orders of magnitude for HCCI engines. The results predicted by the present KIVA AMC code are also consistent with those calculated by the original code using every cell. In the method, progressively coarser grids are used for cells with similar gas properties in the chemistry calculation (up to four neighbour levels) or in the global method, cells are grouped without regard for their locations in the cylinder. Averaged and gradient-preserving remapping techniques used in multi-zone engine simulations were also explored. A parametric study was conducted for determining the model variables, such as the degree of local homogeneity for the multi-grid solvers. The simulation results were compared with experimental data obtained from a Honda engine operated with n-heptane under HCCI conditions for which directly measured in-cylinder temperature and H2O mole fraction data are available. In addition, simulation results were found to agree well with experimental data from a DI diesel engine operated under PCCI conditions with ultra-high EGR rates. It was found that computer time was reduced by a factor of ten for HCCI cases and two to three for DI cases without losing prediction accuracy.