In recent years, the exploration of new combustion technologies has accelerated in response to increasingly stringent emissions regulations and fuel economy demands. Virtual engineering tools, that enable the screening of novel hardware and engine calibrations at the early stage of engine development, have become imperative to meet new emission regulations. One-dimensional engine simulations are used at the start of the design of a new engine to define the overall combustion system geometries. Later, more complex three-dimensional computational fluid dynamics calculations are coupled to one-dimensional engine system codes to optimise initial concept geometries and define a system design ready for prototyping. To provide meaningful results, one-dimensional engine system codes often use empirical-based combustion models to calculate the engine burn rate. Moreover, realistic engine burn rates responses, for the entire engine map and for different calibrations, are required to provide three-dimensional computational fluid dynamics codes with correct boundary conditions during the design optimisation phase. Thus, the burn characteristic of new non-traditional combustion solution, for which little experimental data are available, needs to be initially assumed. To improve virtual development and reduce this uncertainty, the industry’s attention shifted towards quasi-dimensional combustion models capable of providing engine burn rate predictions. Within the quasi-dimensional modelling framework, turbulence models, adding extra user-input variables, are required to capture the effect of different combustion chamber geometries on the engine combustion rate. Rigorous validation of zero-dimensional turbulence models for different engine concepts and calibrations is therefore needed to enable quasi-dimensional combustion models to predict the engine burn rate. An alternative methodology, with limited dependency on previous test data, is required to enhance the exploration of novel combustion strategies and geometric architectures. An available process, based on a quasi-dimensional combustion stochastic reactor model, a one-dimensional engine system model and non-combusting three-dimensional computational fluid dynamics calculations, was used for this work. The approach uses limited non-combusting computational fluid dynamics calculations and a previously developed scaling factor response for the stochastic reactor model turbulence input ( τSRM) to quickly predict the engine rate of heat release. In this work, the scaling factor response was assessed against two different engine variants over a variety of engine operating conditions. Moreover, the same response was used to predict the effect of different bore-to-stroke ratios on the engine combustion rate and knock tolerance. Non-combusting computational fluid dynamics and one-dimensional engine system simulations have been carried out to investigate changes in turbulence characteristics due to different engine variants and bore-to-stroke ratios. It was shown that limited number of non-combusting computational fluid dynamics runs is required to characterise the in-cylinder turbulence for each explored engine variant. The scaling factor response was used to manipulate the turbulence input ( τSRM) resulting in good engine burn rates predictions for the explored engine variants and bore-to-stroke ratios. The presented methodology showed augmented predictive capabilities and has potential to move the engine development towards a less hardware dependent virtual approach, offering a practical solution for the exploration of new engine concepts.
A process for an efficient heat release prediction at the concepts screening stage of gasoline engine development
