Analysis of performance, emissions, and lubrication in a spark-ignition engine fueled with hydrogen gas mixtures.

Hydrogen is one of the main alternative fuels with the greatest potential to replace fossil fuels due to its renewable and environmentally friendly nature. Due to this, the present investigation aims to evaluate the combustion characteristics, performance parameters, emissions, and variations in the characteristics of the lubricating oil. The investigation was conducted in a spark-ignition engine fueled by gasoline and hydrogen gas. Four engine load conditions (25%, 50%, 75%, and 100%) and three hydrogen gas mass concentration conditions (3%, 6%, and 9%) were defined for the study. The investigation results allowed to demonstrate that the injection of hydrogen gas in the gasoline engine causes an increase of 3.2% and 4.0% in the maximum values of combustion pressure and heat release rates. Additionally, hydrogen causes a 2.9% increase in engine BTE. Hydrogen's more efficient combustion process allowed for reducing CO, HC, and smoke opacity emissions. However, hydrogen gas causes an additional increase of 14.5% and 30.4% in reducing the kinematic viscosity and the total base number of the lubricating oil. In addition, there was evidence of an increase in the concentration of wear debris, such as Fe and Cu, which implies higher rates of wear in the engine's internal components.

Estimating the urban environmental impact of gasoline-ethanol blended fuels in a passenger vehicle engine.

A large portion of urban emissions in developing countries come from old gasoline vehicles driven in metropolitan areas. The present study aimed to develop models to estimate the environmental impact of different contents of gasoline and ethanol mixtures (pure gasoline; 25, 50, 75% ethanol blended to gasoline; and 100% ethanol) in a flex-fuel engine. We tested the blended fuel using three different speeds and recorded the GHG emissions and engine output data. The data mining approach was used to develop environmental impact predictive models. The ethanol content in gasoline; the engine rotational speed 900, 2000, and 3000 rpm; and λ were used as attributes. The classification target was the environmental impact concerning the CO2 emission ("low," "average," and "high"). We employed the Random forest algorithm to develop predictive models. The mean values of CO2 concentrations for all studied fuel content were above 2.47% of the volume. The trees' models (accuracy 73%, κ =0.61) showed three alternatives for predicting the environmental impact based on the ethanol blend, the engine rotation, λ, and the air-fuel ratio. Such models might help policymakers develop educational campaigns to reduce short- and medium-term urban commuter traffic pollution in countries that lack suitable urban transportation.

A phenomenological base semi-physical thermodynamic model for the cylinder and exhaust manifold of a natural gas 2-megawatt four-stroke internal combustion engine.

This paper presents the application of a systematic methodology to obtain a semi-physical model of phenomenological base for a 2 MW internal combustion engine to generate electric power operating with natural gas, as a function of the average thermodynamic value normally measured in industrial applications. Specifically, the application of the methodology is focused on the cylinders, exhaust manifold, and turbocharger turbine sections. The proposed model was validated with actual operating data, obtaining an error rate not exceeding 5%, which allow a thermal characterization of the Jenbacher JMS 612 GS-N based on the model. A parametric analysis is conducted; considering the volumetric efficiency, the output electric power, the effective efficiency, the exhaust gas temperature, the turbine mass flow, the specific fuel consumption under the nominal operation conditions, which is 1.16 bar in the gas pressure, 65 °C in the cooling water temperature, 35 °C in the average ambient temperature, and 1500 rpm. The results of this model can be used to evaluate the thermodynamic performance parameters of waste heat recovery systems. On the other hand, new control strategies and the implementation of state observers for the detection and diagnosis of failures can be developed based on the proposed model.