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Premixed charge compression ignition (PCCI) has been shown to be a promising strategy to simultaneously reduce emissions while realizing improved fuel economy. PCCI combustion uses high levels of pre-combustion mixing to lower both NOx and soot emissions by ensuring low equivalence ratio and low flame temperatures. The high level of pre-combustion mixing results in a primarily kinetics controlled combustion process. In this work, optical diagnostics have been applied in a transparent DI diesel engine equipped with the head of Euro5 commercial engine and the last generation CR injection system. In order to realize the PCCI combustion the injection of neat ethanol has been performed in the intake manifold. The engine run in continuous way at 1500 rpm engine speed and commercial diesel fuel has been injected into the cylinder. The PCCI combustion has been analyzed by means of UV- Visible digital imaging and the mixing process, the autoignition of the charge have been investigated.

The increased limitations to both NOx and soot emissions have pushed engine researchers to rediscover gasoline engines. Among the many technologies and strategies, gasoline direct injection plays a key-role for improving fuel economy and engine performance. The paper aims to investigate an extremely complex task such as the idle operating engine condition when the engine runs at very low engine speeds and low engine loads and during the warm-up. Due to the low injection pressure and to the null contribution of the turbocharger, the engine condition is far from the standard points of investigation. Taking into account the warm-up engine condition, the analyses are performed with a temperature of the coolant of 50°C. The paper reports part of a combined numerical and experimental synergic activity aiming at the understanding of the physics of spray/wall interaction within the combustion chamber and particular care is used for air/fuel mixing and the combustion process analyses.

This study aims at building efficient and robust artificial neural networks (ANN) able to reconstruct the in-cylinder pressure of Diesel engines and to identify engine conditions starting from the signal of a low-cost accelerometer placed on the engine block. The accelerometer is a perfect non-intrusive replacement for expensive probes and is prospectively suitable for production vehicles. In this view, the artificial neural network is meant to be efficient in terms of response time, i.e. fast enough for on-line use. In addition, robustness is sought in order to provide flexibility in terms of operation parameters. Here we consider a feed-forward neural network based on radial basis functions (RBF) for signal reconstruction, and a feed-forward multi-layer perceptron network with tan-sigmoid transfer function for signal classification. The networks are trained using measurements from a three-cylinder real engine for various operating conditions.

Within the context of distributed power generation, small size systems driven by spark ignition engines represent a valid and user-friendly choice, that ensures good fuel flexibility. One issue is that such applications are run at part load for extensive periods, thus lowering fuel economy. Employing an inverter (fitted between the generator and load) allows engine operation within a wide range of crankshaft rotational velocity, therefore improving efficiency. For the purpose of evaluating the benefits of this technology within a co-generation framework, two configurations were modeled by using the GT-Power simulation software. After model calibration based on measurements on a small size engine for two-wheel applications, the downsized version was compared to a larger power unit operated at constant engine speed for a scenario that featured up to 10 kW rated power.

The use of direct injection (DI) engines allows a more precise control of the air-fuel ratio, an improvement of fuel economy, and a reduction of exhaust emissions thanks to the ultra-lean combustion due to the charge stratification. These effects can be partially obtained also with an optimized Air Direct Injection that permits to increase the turbulence at low speed and load increasing the combustion stability especially in lean condition. In this paper, a gasoline PFI (named G-PFI), gasoline PFI-methane DI dual fuel (named G-MDF) lean combustion were analyzed. The G-MDF configuration was also compared with a gasoline PFI - air DI (named G-A) configuration in order to distinguish the chemical effect of methane from the direct injection physical effect. The tests were carried out in a small displacement PFI/DI SI engine. The experimental investigation was carried out in a transparent small single-cylinder, spark ignition four-stroke engine.

Improvement of performance and emission of future internal combustion engine for passenger cars is mandatory during the transition period toward their substitution with electric propulsion systems. In middle time, direct injection spark ignition (DISI) engines could offer a good compromise between fuel economy and exhaust emissions. However, abnormal combustion and particularly knock and super-knock are some of the most important obstacles to the improvement of SI engines efficiency. Although knock has been studied for many years and its basic characteristics are clear, phenomena involved in its occurrence are very complex and are still worth of investigation. In particular, the definition of an absolute knock intensity and the precise determination of the knock onset are arduous and many indexes and methodologies has been proposed. In this work, most used methods for knock onset detection from in- cylinder pressure signal have been considered.