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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.

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.

Increasing demands on emissions reduction and efficiency encouraged a progressive introduction of cleaner combustion concepts. "Advanced" diesel combustions offer a high potential for simultaneous reduction of both NOx and soot within the engine through high inlet charge dilution and mixture homogenization. However, the potential benefits of these combustions in terms of emissions are counterbalanced by their high sensitivity to in-cylinder thermodynamic conditions. This sensitivity makes the engines require closed loop combustion control with real-time information about combustion quality. The parameter widely considered as the most important for the evaluation of the combustion quality in internal combustion engines is the cylinder pressure. However, this kind of measure involves an intrusive approach to the cylinder, expensive sensors and a special mounting process.

In the feedforward part of SI engine Air/Fuel control system, the in-cylinder mass air flow rate has to be accurately estimated in order to determine the fuel amount to be injected. Generally, this evaluation is performed either with a dedicated sensor (MAF sensor) or with an indirect evaluation based on the speed-density method. In this paper we propose a soft computing mass air flow estimator for a single-cylinder gasoline engine which is able to estimate, by using the combustion pressure signal, the incoming mass air flow both in steady states and in transient conditions.

The aim of this study is to realize a virtual combustion sensor, that is, a “grey-box” model able to forecast the rate of heat release (ROHR) in a common rail diesel engine, supplied by a modulated injection rate. The model has the following inputs: engine speed, injection pressure, environment conditions and control parameters of the fuel split injection. The idea behind model development is to research ROHR's discriminating features on a Wiebe functions basis using evolutionary algorithms. After this we used a clustering algorithm to find the optimal data set with which we trained the neural network which represents our “grey-box” model. The ROHR model could be used as a virtual combustion sensor in a model based control system for the real-time updating of control parameters. Moreover, it can be used to develop hardware-in-the-loop diesel engine simulation systems. The ROHR model is global, portable, and multi-resolution.

This paper presents a zero dimensional thermodynamic model that predicts the pressure behavior in the combustion chamber of a small compression ignition monocylinder engine. In fact this is a virtual pressure sensor, very simple to be implemented on microcontroller. It cooperates with the electronic control unit to perform the engine management. The aim of this innovative system, just patented, is to act on the control injection strategy improving engine performance, reducing consumption, emissions and acoustic noise.

Comfort requirements, government regulations as well as consumer action groups are pressing the automotive industry to produce less noisy vehicles than in the past. These circumstances become more and more important for off-road and human operating machines forcing engine developers to investigate new and more effective control strategies of noise emissions. This paper concerns with the experimental vibro-acoustic analysis of a small (224 cc) single-cylinder direct-injection diesel engine used for agricultural and industrial applications as well as off road small vehicles. In order to evaluate the engine acoustic behaviour, experimental identification and localization of noise sources were performed at different speed and load engine conditions by several investigating tools. Within them, the intensity technique was chosen because of its peculiarities to be performed “in situ” without a specific anechoic test environment.

A PC-programmable electronic control unit (PECU), able to manage both conventional and future electronic injection systems to make a fixed number of consecutive injections (1 to 5 or more) controlling the injection pressure and the injection pulses duration as well as the separation time or dwell in between was used to study the behaviour of a Bosch common rail injection system both on dynamic spray bench and on engine test bench. The PECU allowed a reduction in the dwell time between consecutive injection pulses from the current value of 1800 μs to 500 μs. Photographic sequences of a five holes mini-sac nozzle making five consecutive injections at 400 - 800 and 1200 bar respectively were taken at ambient pressure and temperature. They showed that both spray penetration and cone angle at all operative conditions are very uniform and stable.