Thermal modelling of modern diesel engines: proposal of a new heat transfer coefficient correlation

Existing methods for predicting heat fluxes and temperatures in internal combustion engines, which take the form of correlations to estimate the heat transfer coefficient on the gas-side of the combustion chamber, are based on methodology developed over the past 50 years, often updated in view of more recent experimental data. The application of these methods to modern diesels engines is questionable because key technologies found in current engines did not exist or were not widely used when those methods were developed. Examples of such technologies include: high-pressure common rail and variable fuel injection strategies including retarded injection for nitrogen oxides emission control; exhaust gas re-circulation; high levels of intake boost pressure provided by a single-or double-stage turbocharger and inter-cooling; multiple valves per cylinder and lower swirl; and advanced engine management systems. This suggests a need for improved predicting tools of thermal conditions, specifically temperature and heat flux profiles in the engine block and cylinder head. In this paper a modified correlation to predict the gas-side heat transfer coefficient in diesel engines is presented. The equation proposed is a simple relationship between Nu and Re calibrated to predict the instantaneous spatially averaged heat transfer coefficient at several operating conditions using air as gas in the model. It was derived from the analysis of experimental data obtained in a modern diesel engine and is supported by a research methodology comprising the application of thermodynamic principles and fundamental equations of heat transfer. The results showed that the new correlation adequately predicted the instantaneous coefficient throughout the operating cycle of a high-speed diesel engine. It also estimated the corresponding cycle-averaged heat transfer coefficient within 10 per cent of the experimental value for the operating conditions considered in the analysis