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Limited and non-regulated emissions of scooters were analysed during several annual research programs of the Swiss Federal Office of Environment (BAFU) *). Small scooters, which are very much used in the congested centers of several cities, are a remarkable source of air pollution. Therefore every effort to reduce the emissions is an important contribution to improve the air quality in urban centers. In the present work detailed investigations of particle emissions of different 2-stroke scooters with direct injection and with carburettor were performed. The nanoparticulate emissions were measured by means of SMPS, (CPC) and NanoMet. Also the particle mass emission (PM) was measured with the same method as for Diesel engines. Extensive analyses of PM-residuum for SOF/INSOF, PAH and toxicity equivalence (TEQ), were carried out in an international project network. Particle mass emission (PM) of 2-S Scooters consists mostly of SOF.

The objectives of the present work are to investigate the regulated and unregulated (particle) emissions of a classical and modern 2-stroke and a typical 4-stroke scooter with different ethanol blend fuels. There is also comparison of two different ethanol fuels: pure ethanol (E) *) and hydrous ethanol (EH) which contains 3.9% water and is denatured with 1.5% gasoline. Special attention is paid in this research to the hydrous ethanol, since the production costs of hydrous ethanol are much less than those for (dry) ethanol. The vehicles are with carburettor and without catalyst, which represents the most frequent technology in Eastern Asia and offers the information of engine-out emissions. Exhaust emissions measurements have been performed with fuels containing ethanol (E), or hydrous ethanol (EH) in the portion of 5, 10, 15 and 20% by volume. During the test systematical analysis of particle mass (PM) and nano-particles counts (NP) were carried out.

Papers in the session cover zero-dimensional, one-dimensional, and quasi-dimensional models for simulation of SI and CI engines with respect to: engine breathing, boosting, and acoustics; SI combustion and emissions; CI combustion and emissions; fundamentals of engine thermodynamics; numerical modeling of gas dynamics; thermal management; mechanical and lubrication systems; system level models for controls; and system level models for vehicle fuel economy and emissions predictions.

Papers in the session cover zero-dimensional, one-dimensional, and quasi-dimensional models for simulation of SI and CI engines with respect to: engine breathing, boosting, and acoustics; SI combustion and emissions; CI combustion and emissions; fundamentals of engine thermodynamics; numerical modeling of gas dynamics; thermal management; mechanical and lubrication systems; system level models for controls; and system level models for vehicle fuel economy and emissions predictions.

A fast time-scale 1-D dynamic diesel particulate filter model capable of resolving the pressure pulsations due to individual cylinder firing events is presented. The purpose of this model is to investigate changes in the firing frequency component of the pulsating exhaust flow at different particulate loadings. Experimental validation data and simulation results clearly show that the magnitude and phase of the firing frequency components are directly correlated to the mass of particulate stored in a diesel particulate filter. This dynamic pressure signal information may prove particularly useful for monitoring particulate load during vehicle operation.

The 1-D model of a radial centripetal turbine was developed for engine simulation to generalize and extrapolate the results of experiments to high pressure ratio or off-design velocity ratio using calibrated tuning coefficients. The model concerns a compressible dissipative flow in a rotating channel. It considers both bladed or vaneless turbine stators and a twin-entry stator for exhaust pulse manifolds. The experiments were used to find values of all model parameters (outlet flow angles, all loss coefficients including an impeller incidence loss) by an original method using repeated regression analysis. The model is suitable for the prediction of a turbocharger turbine operation and its optimization in 1-D simulation codes.

The road transportation sector is undergoing significant changes, and new green scenarios for sustainable mobility are being proposed. In this context, a diversification of the vehicles’ propulsion, based on electric powertrains and/or alternative fuels and technological improvements of the electric vehicles charging stations, are necessary to reduce greenhouse gas emissions. The adoption of internal combustion engines operating with alternative fuels, like methanol, may represent a viable solution for overcoming the limitations of actual grid connected charging infrastructure, giving the possibility to realize off-grid charging stations. This work aims, therefore, at investigating this last aspect, by evaluating the performance of an internal combustion engine fueled with methanol for stationary applications, in order to fulfill the potential demand of an on off-grid charging station.

In recent years, improvements in the fuel economy and exhaust emission performance of internal combustion engines have been increasingly required by regulatory agencies. One of the salient concerns regarding general purpose engines is the larger amount of CO emissions with which they are associated, compared with CO emissions from automobile engines. To reduce CO and other exhaust emissions while maintaining high fuel efficiency, the optimization of total engine system, including various design parameters, is essential. In the engine system optimization process, cycle simulation using 0-D and 1-D engine models are highly useful. To define an optimum design, the model used for the cycle simulation must be capable of predicting the effects of various parameters on the engine performance. In this study, a model for predicting the performance of a general purpose SI (Spark Ignited) engine is developed based on the commercially available engine simulation software, GT-POWER.