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The present paper describes some results of a research project aimed at studying the impact of alternative fuels blends on the emissions and fuel consumption of an Euro 5 automotive diesel engine. Two alternative fuels were chosen for the experiments: RME and GTL. The tests were done in the three most important operating conditions for the engine emission calibration. Moreover, the NOx-PM trade-off by means of EGR sweep was performed in the same operating conditions, in order to evaluate the engine EGR tolerability when burning low sooting fuels as the RME. The investigations put in evidence that the impact of the alternative fuels on modern diesel engines remains significant. This also depends on the interaction between the alternative fuel characteristics and the engine-management strategies, as described in detail in the paper.

The present paper describes the results of a research project aimed at studying the impact of nozzle flow number on a Euro5 automotive diesel engine, featuring Closed-Loop Combustion Control. In order to optimize the trade-offs between fuel economy, combustion noise, emissions and power density for the next generation diesel engines, general trend among OEMs is lowering nozzle flow number and, as a consequence, nozzle hole size. In this context, three nozzle configurations have been characterized on a 2.0L Euro5 Common Rail Diesel engine, coupling experimental activities performed on multi-cylinder and optical single cylinder engines to analysis on spray bomb and injector test rigs. More in detail, this paper deeply describes the investigation carried out on the multi-cylinder engine, specifically devoted to the combustion evolution and engine performance analysis, varying the injector flow number.

In order to meet the increasingly strict emission regulations, several solutions for NOx and PM emissions reduction have been studied. Exhaust gas recirculation (EGR) technology has become one of the more used methods to accomplish the NOx emissions reduction. However, actual control strategies do not consider, in the definition of optimal EGR, its effect on particle size and density. These latter have a great importance both for the optimal functioning of after-treatment systems, but also for the adverse effects that small particles have on human health. Epidemiological studies, in fact, highlighted that the toxicity of particulate particles increases as the particle size decreases. The aim of this paper is to present a Neural Network model able to provide real time information about the characteristics of exhaust particles emitted by a Diesel engine.