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Internal Combustion Engines (ICE) have their use highly disseminated in the most diverse operations. Exhaust gaseous emissions and fuel consumption have been on the scope for decades and therefore the necessity for research on more efficient and lower exhaust emission engines has increased. Considering the cost of equipment and software to develop ICE, the use of computational models is a key strategy to evaluate the behavior of the powertrain/vehicle and lower the instrumentation cost. In this sense, the present work shows the development of an algorithm to obtain a high-resolution crank angle (CA) position of an engine by means of a toothed wheel instead of a high-resolution incremental or absolute encoder. As a result, it enabled the analysis of performance and combustion parameters based on in-cylinder pressure signals acquired through a piezoelectric pressure transducer and the angular position of the crank train referenced by a Hall Effect sensor.

Vegetable oils have been seen as promising surrogates to petroleum diesel in compression ignition internal combustion engines, showing similar performance and combustion characteristics of the fossil fuel. Nevertheless, the use of straight (crude) vegetable oil (SVO) is unfavorable due to its high viscosity, which affects the Sauter Mean Diameter of fuel spray and, consequently, fuel-air mixing process, resulting in incomplete combustion. The SVO heating, as well as transesterification and blending with diesel or additives, are some of the techniques to reduce its viscosity and enable its use. Of these the most simple and direct is the heating and was used in this paper to evaluate the performance and emissions of a diesel engine fueled with preheated soybean oil (PSO) by electrical resistances. The experiments were carried out in a single cylinder four-stroke compression ignition engine with mechanical fuel injection.