A Process for an Efficient Heat Release Prediction at Multiple Engine Speeds and Valve Timings in the Early Stage of Gasoline Engine Development

The increasing need for cleaner and more efficient combustion systems has promoted a paradigm shift in the automotive industry. Virtual hardware and engine calibration screening at the early development stage, has become the most effective way to reduce the time necessary to bring new products to market. Virtual engine development processes need to provide realistic engine combustion rate responses for the entire engine map and for different engine calibrations. Quasi Dimensional (Q-D) combustion models have increasingly been used to predict engine performance at multiple operating conditions. The physics-based Q-D turbulence models necessary to correctly model the engine combustion rate within the Q-D combustion model framework are a computationally efficient means of capturing the effect of port and combustion chamber geometry on performance. A rigorous method of correlating the effect of air motion on combustion parameters such as heat release is required to enable novel geometric architectures to be assessed to deliver future improvements in engine performance.

A previously assessed process using a combination of a 0-D combustion Stochastic Reactor Model (SRM), provided by LOGESoft, a 1-D engine system model and non-combusting, ‘cold’ CFD is used. The approach uses a single baseline CFD run and a user developed scalar mixing time (τ_SRM) response to quickly predict the Rate of Heat Release (RoHR). In this work, the physically-based response for τ_SRM has been further developed to consider the effect of Variable Valve Timing (VVT) for a variety of engine operating conditions. Cold CFD and 1-D engine simulations have initially been carried out to investigate changes in Turbulent Kinetic Energy (k) and its dissipation (ε) caused by VVT changes, allowing the engine Rate of Heat Release (RoHR) to be predicted. The change in the intake flow velocity was correlated to the scalar mixing time, τ_SRM resulting in a good engine RoHR prediction at the explored conditions.