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Knock occurrence and fuel enrichment, which is required at high engine speed and load to limit the turbine inlet temperature, are the major obstacles to further increase performance and efficiency of down-sized turbocharged spark ignited engines. A technique that has the potential to overcome these restrictions is based on the injection of a precise amount of water within the mixture charge that can allow to achieve important benefits on knock mitigation, engine efficiency, gaseous and noise emissions. One of the main objectives of this investigation is to demonstrate that water injection (WI) could be a reliable solution to advance the spark timing and make the engine run at leaner mixture ratios with strong benefits on knock tendency and important improvement on fuel efficiency.

In the present paper, two different methodologies are adopted and critically integrated to analyze the knock behavior of a last generation small size spark ignition (SI) turbocharged VVA engine. Particularly, two full load operating points are selected, exhibiting relevant differences in terms of knock proximity. On one side, a knock investigation is carried out by means of an Auto-Regressive technique (AR model) to process experimental in-cylinder pressure signals. This mathematical procedure is used to estimate the statistical distribution of knocking cycles and provide a validation of the following 1D-3D knock investigations. On the other side, an integrated numerical approach is set up, based on the synergic use of 1D and 3D simulation tools. The 1D engine model is developed within the commercial software GT-Power™. It is used to provide time-varying boundary conditions (BCs) for the 3D code, Star-CD™.

During the last years, a number of techniques aimed at the experimental identification of the knocking onset in Spark-Ignition (SI) Internal Combustion Engines have been proposed. Besides the traditional procedures based on the processing of in-cylinder pressure data in the frequency domain, in the present paper two innovative methods are developed and compared. The first one is based on the use of statistical analysis by applying an Auto Regressive Moving Average (ARMA) technique, coupled to a prediction algorithm. It is shown that such parametric model, applied to the instantaneous in-cylinder pressure measurements, is highly sensitive to knock occurrence and is able to identify soft or heavy knock presence in different engine operating conditions. An alternative, more expensive procedure is developed and compared to the previous one.