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In this research work, a comprehensive combustion analysis has been conducted to evaluate the performance of a low speed diesel engine (M8/1 Lister) using biodiesel fuel. Waste vegetable cooking oil as an alternative fuel. Biodiesel obtained from waste vegetable cooking oil (WCO) as an alternative fuel. The properties of biodiesel produced from WCO was measured based on ASTM standards. In order to compare brake power, torques , brake specific fuel consumption (BSFC) and concentration of the UHC and CO emissions of the engine, it has been tested under same load of Dynamometer(5 levels) and biodiesel fuel blends (levels)) at constant engine speed(750 rpm). The results were found to be very comparable. An artificial neural network (ANN) was developed based on the collected data of this work. Multi layer perceptron network (MLP) was used for nonlinear mapping between the input and the output parameters. Different activation functions and several rules were used to assess the percentage error between the desired and the predicted values. The results showed that the training algorithm of Back Propagation was sufficient in predicting the engine torque, brake power, specific fuel consumption and exhaust gas components for different engine loads and different fuel blends ratios.

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Concerning the adverse environmental impacts of fossil fuel consumption, many investigations have been performed on choosing more environmentally friendly fuel alternatives and sustainable resources. In this regard, hydrogen is considered to be one of the promising alternative fuels as its combustion features are the most similar to fossil fuels and it also falls into the category of renewable and clean fuels. This article studies the simulation of hydrogen-diesel combustion in heavy duty engine at full load and speed of 1600 rpm. All engine features including speed, spray angle, spray duration and input power are held fixed in the simulation. Variable parameter is the ratio of mass or hydrogen energy to diesel. Depending on input power of diesel, hydrogen is changed from 0% (pure diesel) to 70% (i.e. 70% is supplied from the input power of hydrogen and the remaining 30% from diesel fuel). The results of simulation show that hydrogen substitution with diesel at the best state leads to reduction of pollutants such as nitric oxides, carbon dioxide, unburned hydrocarbon, soot and carbon monoxide to 8%, 14%, 54%, 14% and 70%, respectively. This substitution however causes the reduction of indicated efficiency to 2.8%. Hydrogen substitution with diesel can also postpone the combustion, and resulting to increase PRR and HRR; however, this pressure enhancement does not lead to knocking.

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Concerns for climate change, reduction of greenhouse gas emission and environmental pollution, besides economically dependency on fossil fuels and political aspect motivate governments and policy makers to take into account replacing usual vehicle with alternative fuel vehicles (AFVs) such as Compressed Natural Gas Vehicles (CNGV) and Gasoline-Electric Hybrid Vehicles (GEHV). The air pollution in Tehran is a serious concern that based on this problem, CNGV has been introduced to Iranian market from 10 years ago. On the other hand, with the approval and notification of the removal of the electric vehicle importation’s tariff law, GEHV has been entered into the market of Iran as a new entrant. The purposes of this paper is to identify the effective factors to choose AFVs for drivers in Tehran and the assessment of effects of the incentive policies that increase AFV shares and computing their willingness to pay (WTP) for AFV under different incentives. This study designed a questionnaire which includes 3 parts: current vehicle features, dominant travel characteristics, socio-economic properties and the prioritization of effective factors on new vehicle purchase, and the tendency of AFVs choice with different scenarios representing different features. A random sample of 365 respondents was interviewed in a face-to-face survey in February 2016 in the technical inspection centers and in compressed natural gas stations. Finally, for the determination of effective factors on current and new vehicle purchase with revealed preference information and the assessment of AFVs usage tendency with stated preference information, the Multinomial Logit models have been used and WTPs are calculated. The incentive policy in Tehran, like previous studied countries, was the most influential factor in motivating consumers to buy AFVs in comparison to improvement of AFV specifications. The results show that drivers’ WTP is 5 MT for free access to even-odd area for CNGV and 12 MT for GEHV, also WTP for free access to pricing area in Tehran central business district is equal to 10 MT for CNGV; i.e. people tend to pay this extra cost for AFVs to access to pricing areas. These values are comparable with similar studies in cities located in developed countries. However, the results of this study show that WTP for fuel cost in Iran is considerably less than WTP of people driving in developed countries. The fuel cost and access time to gas stations are influential variables on CNGV choice. The vehicle acceleration and driving range are influential variables on GEHV choice.