Hybrid vehicle engines modified for high exhaust gas
recirculation (EGR) are a good choice for high efficiency and low
NOx emissions. Such operation can result in an HEV when a downsized
engine is used at high load for a large fraction of its run time to
recharge the battery or provide acceleration assist. However, high
EGR will dilute the engine charge and may cause serious performance
problems such as incomplete combustion, torque fluctuation, and
engine misfire. An efficient way to overcome these drawbacks is to
intensify tumble leading to increased turbulent intensity at the
time of ignition. The enhancement of turbulent intensity will
increase flame velocity and improve combustion quality, therefore
increasing engine tolerance to higher EGR.
It is accepted that the detailed experimental characterization
of flow field near top dead center (TDC) in an engine environment
is no longer practical and cost effective. Instead, CFD is more
convenient, more economical, and more versatile to study the
in-cylinder flow physics if its accuracy is validated with
experimental results. To achieve the goal of increasing tolerance
to EGR, this work reports investigations of intake port design
simulation.
Part 1 of this two-part paper presents a CFD simulation
methodology. It includes a preliminary study of software selection
and a systematic validation study to verify the accuracy of the CFD
tool. The validations were performed through the comparison with
PIV experimental tests. An assessment of the standard k-ε (SKE),
renormalization group k-ε (RNG), and Reynolds stress model (RSM)
turbulence models were performed for a series of intake valve lift
and intake pressure combination. The results indicate that SKE is
the best suited over RNG and RSM models as it is most accurate, at
least for the current test conditions. The investigation of grid
independence and parameter sensitivity study is also presented. The
developed CFD methodology is applied, in Part 2, for a new intake
port design with a transient study of real engine operation
conditions to determine the effectiveness of the optimized
shape.