A fully coupled computational fluid dynamics and multi-zone model with detailed chemical kinetics for the simulation of premixed charge compression ignition engines

Abstract

Modelling the premixed charge compression ignition (PCCI) engine requires a balanced approach that captures both fluid motion as well as low- and high-temperature fuel oxidation. A fully integrated computational fluid dynamics (CFD) and chemistry scheme (i.e. detailed chemical kinetics solved in every cell of the CFD grid) would be the ideal PCCI modelling approach, but is computationally very expensive. As a result, modelling assumptions are required in order to develop tools that are computationally efficient, yet maintain an acceptable degree of accuracy. Multi-zone models have been previously shown accurately to capture geometry-dependent processes in homogeneous charge compression ignition (HCCI) engines. In the presented work, KIVA-3V is fully coupled with a multi-zone model with detailed chemical kinetics. Computational efficiency is achieved by utilizing a low-resolution discretization to solve detailed chemical kinetics in the multi-zone model compared with a relatively high-resolution CFD solution. The multi-zone model communicates with KIVA-3V at each computational timestep, as in the ideal fully integrated case. The composition of the cells, however, is mapped back and forth between KTVA-3V and the multi-zone model, introducing significant computational time savings. The methodology uses a novel re-mapping technique that can account for both temperature and composition non-uniformities in the cylinder. Validation cases were developed by solving the detailed chemistry in every cell of a KIVA-3V grid. The new methodology shows very good agreement with the detailed solutions in terms of ignition timing, burn duration, and emissions.

Experimental Validation of Combustion Models for Diesel Engines Based on Tabulated Kinetics in a Wide Range of Operating Conditions

“…Fuel is delivered by a single injection with the SOI at approximately 25 CAD BTDC. The TWM model was used in PCCI combustion, since it is expected that effects of turbulence-chemistry interaction under such operating mode can be at first approximation neglected [33,34]. However, in order to better capture the combined pressure/temperature effects on the ignition process, a higher temperature and pressure discretization for the chemistry table was used, whose details are reported in Tab.…”

A Two-Zone Multigrid Model for SI Engine Combustion Simulation Using Detailed Chemistry

“…The multigrid (MG) model [13] is designed to reduce the frequency of calling the CHEMKIN solver, which is the most time-consuming part of simulation when detailed chemistry is used. The MG model groups thermodynamically similar cells via a mapping procedure into one "grouped cell" for the CHEMKIN calculation, followed by a procedure to redistribute the group information back onto the individual cells using remapping.…”

“…The MG model groups thermodynamically similar cells via a mapping procedure into one "grouped cell" for the CHEMKIN calculation, followed by a procedure to redistribute the group information back onto the individual cells using remapping. The grouping region (searching level) is either fixed [13] or determined adaptively [15] accounting for the local inhomogeneities in the thermodynamic conditions to deal with the nonuniform spatial distribution of thermochemistry properties. The concept of an adaptive neighbor search is further illustrated in Figure 1 using a 2D schematic mesh.…”

“…When adaptive searching is used, the searching level at each time step is determined considering the inhomogeneity of all the computational cells. The grouping criteria considered in the present work include the cell temperature and progress equivalence ratio [13,15]. In the present work, a difference in temperature of 20 K and a difference in equivalence ratio of 10% were used to determine if cells are thermodynamically "similar" [15].…”

“…for example, multizone models [13], dynamic cell clustering [14], and adaptive multigrid chemistry (AMC) [15]; (4) solve the ODEs using alternative faster numerical schemes: for example, [16].…”