Analysis of Biodiesel Spray Combustion in Internal-Combustion Engine using Multidimensional Models
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Abstract
With the rapid scale expansion of the first generation of bio-liquid fuels, its impact on the prices of agricultural products, food security and the environment has begun to emerge and attracted extensive attention from governments and academia. A new multi-dimensional model of biodiesel spray combustion in an internal combustion (IC) engine is designed. Firstly, the BP neural network mining model is used to extract the spray combustion data of the IC engine. Then, based on the combustion data of biodiesel load in an internal combustion engine, burning rate and heat release, the principle of spray combustion of biodiesel is analyzed. Finally, from the two aspects of gas-phase control and liquid phase control, a multi-dimensional model of biodiesel spray combustion in IC engine is established and the spray combustion characteristics of biodiesel in IC engine are analyzed. The research results show that the model can effectively analyze the effect of load and fuel temperature on the spray combustion characteristics of biodiesel and the results of the model are almost the same as the actual data and the calculation accuracy is high. It is an effective method for studying the spray combustion characteristics of biodiesel.
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