Search Results

The numerical reconstruction of the liquid jet generated by a multi-hole injector, operating in flash-boiling conditions, has been developed by means of a Eulerian- Lagrangian CFD code and validated thanks to experimental data collected with schlieren and Mie scattering imaging techniques. The model has been tested with different injection parameters in order to recreate various possible engine thermodynamic conditions. The work carried out is framed in the growing interest present around the gasoline direct-injection systems (GDI). Such technology has been recognized as an effective way to achieve better engine performance and reduced pollutant emissions. High-pressure injectors operating in flashing conditions are demonstrating many advantages in the applications for GDI engines providing a better fuel atomization, a better mixing with the air, a consequent more efficient combustion and, finally, reduced tailpipe emissions.

This paper deals with the combustion characteristics and exhaust emissions of a diesel engine fuelled with conventional diesel fuel and a biodiesel blend, in particular a 20% v/v concentration of rapeseed methyl ester (RME) mixed with diesel fuel. The investigation was carried out on a prototype three-cylinder engine with 1000 cc of displacement for quadricycle applications. The engine is equipped with a direct common-rail injection system that reaches a maximum pressure of 1400 bar. The engine was designed to comply with Euro 4 and BS IV exhaust emission regulations without a diesel particulate filter. Both in-cylinder pressure and rate of heat release traces were analyzed at different engine speeds and loads. Gaseous emissions were measured at the exhaust. A smoke meter was used to measure the particulate matter concentration. The sizing and the counting of the particles were performed by means of an engine exhaust particle sizer spectrometer.

In the arduous aim to reduce petroleum fuel consumption and toxic emissions, gaseous fuels can represent an alternative solution for heavy duty applications with respect to conventional liquid fuels. At the same time, the imposition of more stringent emission regulations in the transport sector, is a crucial aspect to be taken into account during the development of future gas engines. Aim of the present paper was to characterize a heavy duty spark ignition engine, under development for Euro VI compliance, with a particular focus on exhaust particulate emissions. In this sense, the engine was installed on a dynamic test bench, accurately instrumented to analyze combustion evolution, performance and exhaust pollutant emissions, along the World Harmonized Transient Cycle (WHTC).

Gas engines (fuelled with CNG, LNG or Biogas) for generation of power and heat are, to this date, taking up larger shares of the market with respect to diesel engines. In order to meet the limit imposed by the TA-Luft regulations on stationary engines, lean combustion represents a viable solution for achieving lower emissions as well as efficiency levels comparable with diesel engines. Leaner mixtures however affect the combustion stability as the flame propagation velocity and consequently heat release rate are slowed down. As a strategy to deliver higher ignition energy, an active pre-chamber may be used. This work focuses on assessing the performance of a pre-chamber combustion configuration in a stationary heavy-duty engine for power generation, operating at different loads, air-to-fuel ratios and spark timings.

Diesel will continue to be an indispensable energy carrier for the car fleet CO2 emission targets in the short-term. This is particularly relevant for heavy-duty vehicles as for mid-size cars and SUVs. Looking at the latest technology achievements on the after-treatment systems, it can be stated that the concerning about the NOx emission gap between homologation test and real road use is basically solved, while the future challenge for diesel survival is to keep its competitiveness in the CO2 vs cost equation in comparison to other propulsion systems. The development of the combustion system design still represents an important leverage for further efficiency and emissions improvements while keeping the current excellent performance in terms of power density and low-end torque.

This study aims at building an efficient and robust radial basis function (RBF) artificial neural network (ANN), to reconstruct the in-cylinder pressure of a diesel engine 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. The RBF network is trained using measurements from different engine operating conditions. Training data are composed of time series from the accelerometer and corresponding measured in-cylinder pressure signals. The RBF network is then validated using data not included in training and the results show good correspondence between measured and reconstructed pressure signal. Various network parameters are used to optimize the network quality.

In order to meet the requirements in the stringent emission regulations, more and more research work has been focused on homogeneous charge compression ignition (HCCI) and partially premixed combustion (PPC) or partially premixed compression ignition (PCCI) as they have the potential to produce low NOx and soot emissions without adverse effects on engine efficiency. The mixture formation and charge stratification influence the combustion behavior and emissions for PPC/PCCI, significantly. An ultra-high speed burst-mode laser is used to capture the mixture formation process from the start of injection until several CADs after the start of combustion in a single cycle. To the authors’ best knowledge, this is the first time that such a high temporal resolution, i.e. 0.2 CAD, PLIF could be accomplished for imaging of the in-cylinder mixing process. The capability of resolving single cycles allows for the influence of cycle-to-cycle variations to be eliminated.