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In order to meet the stricter and stricter emission regulations, cleaner combustion concepts for Diesel engines are being progressively introduced. These new combustion approaches often requires closed loop control systems with real time information about combustion quality. The most important parameter for the evaluation of combustion quality in internal combustion engines is the in-cylinder pressure, but its direct measurement is very expensive and involves an intrusive approach to the cylinder. Previous researches demonstrated the direct relationship existing between in-cylinder pressure and engine block vibration signal and several authors tried to reconstruct the pressure cycle on the basis of information coming from accelerometers mounted on engine block. This paper proposes a method, based on the analysis of the engine vibration signal, for the diagnosis of combustion process in a Diesel engine.

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.

Gasoline direct injection (GDI) combustion with un-throttled lean stratified operation allows to reduce engine toxic emissions and achieve significant benefits in terms of fuel consumption. However, use of gasoline stratified charges can lead to several problems, such as a high cycle-to-cycle variability and increased particle emissions. Use of multiple injection strategies allows to mitigate these problems, but it requires the injection of small fuel amounts forcing the traditional solenoid injectors to work in their “ballistic” region, where the correlation between coil energizing time and injected fuel amount becomes highly not linear. In the present work a closed-loop control system able to manage the delivery of small quantities of fuel has been introduced. The control system is based on a particular feature found on the coil voltage command signal during the de-energizing phase.