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These last years, much of researches were carried out to find the appropriate substitution fuel to the fossil fuels. The use of biofuel prepared from non-edible vegetable oils are becoming a promising source to produce a fuel for diesel engine, commonly referred to as “biodiesel”. Considering the high oil extraction yield (around 40%) and the great quantity of pistacia lentiscus (PL) trees available in arid and semi-arid areas of Mediterranean countries, it is selected in the present work to study the biodiesel prepared from PL oil. PL biodiesel is obtained by converting PL seed oil with a single-step homogenous alkali catalyzed transesterification process. PL biodiesel characterization, according to the standard methods, shows that the physicochemical properties are comparable to those of conventional diesel fuel. In a second part, a single cylinder air-cooled, DI diesel engine is used to test PL biodiesel at 1500 rpm under various engine load conditions.

Knock is a major technological constriction of natural gas spark ignition engines. Nowadays, it is widely accepted that knock is due to auto-ignition in the end gas region. Knock can occur for different reasons, which could be related to the engine itself (design and settings) or to the gas composition (or the gas quality). In a previous study the effect of engine settings on knock in a C.F.R. SI engine fuelled by pure methane was established by using a knock indicator, based on the evaluation of the energy of end gases. The paper deals with knock limit prediction from natural gas quality in a C.F.R. engine. A 2-zone thermodynamic model was developed in order to predict knocking conditions by evaluating a knock indicator. The model relies on some standard assumptions. Ignition delay was expressed as a function of engine settings, and a physical correlation for the heat release rate model was used.

Numerical simulation is a useful and a cost-effective tool for engine cycle prediction. In the present study, a dual Wiebe function is used to approximate the heat release rate in a DI, naturally aspirated diesel engine fuelled with eucalyptus biodiesel/diesel fuel blends and operated at various engine loads. This correlation is fitted to the experimental heat release rate at various operating conditions (fuel nature and engine load) using a least squares regression to find the unknown parameters. The main objective of this study is to propose a model to predict the Wiebe function parameters for more general operating conditions, not only those experimentally tested. For this purpose, an artificial neural network (ANN) is developed on the basis of the experimental data. Engine load and eucalyptus biodiesel/diesel fuel blend are the input layer, while the six parameters of the dual Wiebe function are the output layer.

The crude oil depletion, as well as aspects related to environmental pollution and global warming has caused researchers to seek alternative fuels. Biogas is one of the most attractive available fuels. It is of great interest both economically and ecologically. However, it faces problems that may compromise its industrial use. The dual-fuel engines have been investigated as a technique for the recovery of these gases and finding solutions to these problems. In the present work, performance and emissions of a direct injection diesel engine were first evaluated in conventional mode and dual fuel mode. The effect of biogas composition, based on methane content, is then examined. Also, dual fuel operation with regard to knock is investigated. The results show that, up to 95% of engine full load, the brake thermal efficiency (BTE) is lower in dual fuel mode. In terms of the specific consumption, although at high load the gap is much less, it is more significant in case of dual fuel mode.

Near-term advances in spark ignition (SI) engine technology (e.g., variable value lift [VVL], gasoline direct injection [GDI], cylinder deactivation, turbo downsizing) for passenger vehicles hold promise of delivering significant fuel savings for vehicles of the immediate future. Similarly, trends in transmissions indicate higher (8-speed, 9-speed) gear numbers, higher spans, and a focus on downspeeding to improve engine efficiency. Dual-clutch transmissions, which exhibit higher efficiency in lower gears, than the traditional automatics, and are being introduced in the light-duty vehicle segment worldwide. Another development requiring low investment and delivering immediate benefits has been the adaptation of start-stop (micro hybrids or idle engine stop technology) technology in vehicles today.

CHP power plants, supplied by natural gas, have a great interest due to more and more stringent environmental regulations. Natural gas has a low C/H ratio resulting in low CO2 emissions in spark ignition engines. For economical reasons, CHP gas engines are normally designed to operate under their optimal settings. Small variations in the composition of the supplied gas can then lead to knock occurrence. In this paper, a preventive knock device is developed for CHP power plants. It is based on the instantaneous measure of the Methane Number (MN) of the supplied gas. The measure is performed through an online MN gas sensor (it measures as well Wobbe index and the calorific value of the supplied gas). Prediction of knock, following the MN of the gas is developed in previous works. Correction of knock is performed through an engine map, established thanks to numerical simulations.

This paper focuses on the prediction of thermal losses and indicated performance in modern automotive engines. In a previous study, a complete simulation software was developed in order to both predict the car cabin blown air temperature and simulate the fluid circuits temperature. The two-zone, 0-dimensionnal combustion model presented in this paper aims to enhance this software. Theoretical overview reveals that thermal losses can be deduced from a predictive correlation of indicated performance. This correlation is established with a statistical tool and empirical coefficients are proposed. As a result of this study, the simulation software becomes a real-time computing tool that considers variable parameters previously neglected.