Gasoline fuelled partially premixed compression ignition in a light duty multi cylinder engine: A study of low load and low speed operation

The objective of this study was to examine the operating characteristics of a light duty multi cylinder compression ignition engine with regular gasoline fuel at low engine speed and load. The effects of fuel stratification by means of multiple injections as well as the sensitivity of auto-ignition and burn rate to intake pressure and temperature are presented. The measurements used in this study included gaseous emissions, filter smoke opacity and in-cylinder indicated information. It was found that stable, low emission operation was possible with raised intake manifold pressure and temperature, and that fuel stratification can lead to an increase in stability and a reduced reliance on increased temperature and pressure. It was also found that the auto-ignition delay sensitivity of gasoline to intake temperature and pressure was low within the operating window considered in this study. Nevertheless, the requirement for an increase of pressure, temperature and stratification in order to achieve auto-ignition time scales small enough for combustion in the engine was clear, using pump gasoline. Copyright © 2009 SAE International.

Biodiesel de mamona no diesel interior e metropolitano em trator agrícola

A demanda de recursos energéticos pelos sistemas de produção, aliada à escassez dos combustíveis fósseis, tem motivado a produção do Biodiesel, que é um combustível obtido de fontes renováveis. O objetivo deste trabalho foi realizar dois ensaios: o primeiro dinâmico, para avaliar o desempenho operacional utilizando como parâmetro o consumo de combustível, e o segundo, estático, para mensurar a opacidade da fumaça (material particulado) do motor de um trator agrícola, operando com diesel metropolitano e interior misturados ao Biodiesel de mamona, em sete proporções. O trabalho foi conduzido no Departamento de Engenharia Rural da UNESP/Jaboticabal - SP. Os resultados mostraram que o tipo de diesel influenciou no consumo de combustível e na opacidade da fumaça, sendo o diesel metropolitano de melhor qualidade; observou-se, também, que à medida que a proporção de Biodiesel aumentou, o mesmo ocorreu para o consumo de combustível; entretanto, a opacidade da fumaça reduziu com o acréscimo de Biodiesel até B75.

Desempenho operacional e opacidade da fumaça do trator agrícola em função do tipo de biodiesel (soja x murumuru) em operação de preparo do solo

Pós-graduação em Agronomia (Ciência do Solo) - FCAV

Efeito de biodeisel de mamona no diesel interior e metropolitano em trator agrícola

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Biodiesel de mamona em trator agrícola na operação de preparo do solo

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Biodiesel de dendê, mamona e tucumã no desempenho de um trator agrícola na operação de preparo do solo

Pós-graduação em Agronomia (Ciência do Solo) - FCAV

Biodiesel de buriti em trator: desempenho em função do tipo de diesel e da proporção de mistura na operação de preparo do solo

Pós-graduação em Agronomia (Ciência do Solo) - FCAV

Effects of engine cooling water temperature on performance and exhaust emission characteristics of a multi-cylinder CI engine operated with Jatropha-Butanol blend

Renewable alternatives such as biofuels and optimisation of the engine operating parameters can enhance engine performance and reduce emissions. The temperature of the engine coolant is known to have significant influence on engine performance and emissions. Whereas much existing literature describes the effects of coolant temperature in engines using fossil derived fuels, very few studies have investigated these effects when biofuel is used as an alternative fuel. Jatropha oil is a non-edible biofuel which can substitute fossil diesel for compression ignition (CI) engine use. However, due to the high viscosity of Jatropha oil, technique such as transesterification, preheating the oil, mixing with other fuel is recommended for improved combustion and reduced emissions. In this study, Jatropha oil was blended separately with ethanol and butanol, at ratios of 80:20 and 70:30. The fuel properties of all four blends were measured and compared with diesel and jatropha oil. It was found that the 80% jatropha oil + 20% butanol blend was the most suitable alternative, as its properties were closest to that of diesel. A 2 cylinder Yanmar engine was used; the cooling water temperature was varied between 50°C and 95°C. In general, it was found that when the temperature of the cooling water was increased, the combustion process enhanced for both diesel and Jatropha-Butanol blend. The CO2 emissions for both diesel and biofuel blend were observed to increase with temperature. As a result CO, O2 and lambda values were observed to decrease when cooling water temperature increased. When the engine was operated using diesel, NOX emissions correlated in an opposite manner to smoke opacity; however, when the biofuel blend was used, NOX emissions and smoke opacity correlated in an identical manner. The brake thermal efficiencies were found to increase slightly as the temperature was increased. In contrast, for all fuels, the volumetric efficiency was observed to decrease as the coolant temperature was increased. Brake specific fuel consumption was observed to decrease as the temperature was increased and was higher on average when the biofuel was used, in comparison to diesel. The study concludes that the effects of engine coolant temperature on engine performance and emission characteristics differ between biofuel blend and fossil diesel operation. The coolant temperature needs to be optimised depending on the type of biofuel for optimum engine performance and reduced emissions.

Effects of engine cooling water temperature on performance and emission characteristics of a CI engine operated with biofuel blend

The temperature of the coolant is known to have significant influence on engine performance and emissions. Whereas existing literature describes the effects of coolant temperature in engines using fossil derived fuels, very few studies have investigated these effects when biofuel is used. In this study, Jatropha oil was blended separately with ethanol and butanol. It was found that the 80% jatropha oil + 20% butanol blend was the most suitable alternative, as its properties were closest to that of fossil diesel. The coolant temperature was varied between 50°C and 95°C. The combustion process enhanced for both diesel and biofuel blend, when the coolant temperature was increased. The carbon dioxide emissions for both diesel and biofuel blend were observed to increase with temperature. The carbon monoxide, oxygen and lambda values were observed to decrease with temperature. When the engine was operated using diesel, nitrogen oxides emissions correlated in an opposite manner to smoke opacity; however, nitrogen oxides emissions and smoke opacity correlated in an identical manner for biofuel blend. Brake specific fuel consumption was observed to decrease as the temperature was increased and was higher on average when the biofuel was used. The study concludes that both biofuel blend and fossil diesel produced identical correlations between coolant temperature and engine performance. The trends of nitrogen oxides and smoke emissions with cooling temperatures were not identical to fossil diesel when biofuel blend was used in the engine.

A Decision-Tree-Based Approach to Smoke Spike Detection in a Heavy-Duty Diesel Engine

Smoke spikes occurring during transient engine operation have detrimental health effects and increase fuel consumption by requiring more frequent regeneration of the diesel particulate filter. This paper proposes a decision tree approach to real-time detection of smoke spikes for control and on-board diagnostics purposes. A contemporary, electronically controlled heavy-duty diesel engine was used to investigate the deficiencies of smoke control based on the fuel-to-oxygen-ratio limit. With the aid of transient and steady state data analysis and empirical as well as dimensional modeling, it was shown that the fuel-to-oxygen ratio was not estimated correctly during the turbocharger lag period. This inaccuracy was attributed to the large manifold pressure ratios and low exhaust gas recirculation flows recorded during the turbocharger lag period, which meant that engine control module correlations for the exhaust gas recirculation flow and the volumetric efficiency had to be extrapolated. The engine control module correlations were based on steady state data and it was shown that, unless the turbocharger efficiency is artificially reduced, the large manifold pressure ratios observed during the turbocharger lag period cannot be achieved at steady state. Additionally, the cylinder-to-cylinder variation during this period were shown to be sufficiently significant to make the average fuel-to-oxygen ratio a poor predictor of the transient smoke emissions. The steady state data also showed higher smoke emissions with higher exhaust gas recirculation fractions at constant fuel-to-oxygen-ratio levels. This suggests that, even if the fuel-to-oxygen ratios were to be estimated accurately for each cylinder, they would still be ineffective as smoke limiters. A decision tree trained on snap throttle data and pruned with engineering knowledge was able to use the inaccurate engine control module estimates of the fuel-to-oxygen ratio together with information on the engine control module estimate of the exhaust gas recirculation fraction, the engine speed, and the manifold pressure ratio to predict 94% of all spikes occurring over the Federal Test Procedure cycle. The advantages of this non-parametric approach over other commonly used parametric empirical methods such as regression were described. An application of accurate smoke spike detection in which the injection pressure is increased at points with a high opacity to reduce the cumulative particulate matter emissions substantially with a minimum increase in the cumulative nitrogrn oxide emissions was illustrated with dimensional and empirical modeling.

Analysis and Prediction of Transient Opacity Spikes Using Dimensional Modeling

Dimensional modeling, GT-Power in particular, has been used for two related purposes-to quantify and understand the inaccuracies of transient engine flow estimates that cause transient smoke spikes and to improve empirical models of opacity or particulate matter used for engine calibration. It has been proposed by dimensional modeling that exhaust gas recirculation flow rate was significantly underestimated and volumetric efficiency was overestimated by the electronic control module during the turbocharger lag period of an electronically controlled heavy duty diesel engine. Factoring in cylinder-to-cylinder variation, it has been shown that the electronic control module estimated fuel-Oxygen ratio was lower than actual by up to 35% during the turbocharger lag period but within 2% of actual elsewhere, thus hindering fuel-Oxygen ratio limit-based smoke control. The dimensional modeling of transient flow was enabled with a new method of simulating transient data in which the manifold pressures and exhaust gas recirculation system flow resistance, characterized as a function of exhaust gas recirculation valve position at each measured transient data point, were replicated by quasi-static or transient simulation to predict engine flows. Dimensional modeling was also used to transform the engine operating parameter model input space to a more fundamental lower dimensional space so that a nearest neighbor approach could be used to predict smoke emissions. This new approach, intended for engine calibration and control modeling, was termed the "nonparametric reduced dimensionality" approach. It was used to predict federal test procedure cumulative particulate matter within 7% of measured value, based solely on steady-state training data. Very little correlation between the model inputs in the transformed space was observed as compared to the engine operating parameter space. This more uniform, smaller, shrunken model input space might explain how the nonparametric reduced dimensionality approach model could successfully predict federal test procedure emissions when roughly 40% of all transient points were classified as outliers as per the steady-state training data.