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Improvement of an SI Engine Performance Using Modified Al-Doura Pool Gasoline Formulae: Simulation Study

机译:使用改进的Al-Doura池汽油配方改进SI发动机性能的仿真研究

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This paper presents the results of simulation study conducted on a water-cooled, single-cylinder, 4-stroke spark ignition engine. The engine was simulated using both original fuel produced in Iraq and a modified formula made by the authors. The results show great improvement in some of the fuel properties like calorific value, sulfur content, total water content, MON and RON and gum content. On the engine side, the engine power, torque, combustion efficiency, sulfur dioxide levels were greatly improved, while the heat loss, bsfc and NOx emissions increased. Further, Artificial Neural Networks (ANN) was used to predict the engine performance and emission characteristics of the engine. Separate models were developed for performance parameters as well as emission characteristics. ANN results showed that there is a good correlation between the ANN predicted values and the experimental values for various engine performance parameters and exhaust emission characteristics and the relative mean error values were within 5 %, which is acceptable.
机译:本文介绍了在水冷单缸四冲程火花点火发动机上进行的仿真研究的结果。使用伊拉克生产的原始燃料和作者修改后的公式对发动机进行了仿真。结果表明,在某些燃料性能方面,例如热值,硫含量,总水含量,MON和RON以及口香糖含量有了很大的改善。在发动机方面,发动机的功率,扭矩,燃烧效率,二氧化硫含量得到了极大的改善,而热量损失,bsfc和NOx排放却增加了。此外,人工神经网络(ANN)用于预测发动机性能和发动机排放特性。针对性能参数和排放特性开发了单独的模型。人工神经网络的结果表明,各种发动机性能参数和废气排放特性的人工神经网络预测值与实验值之间具有良好的相关性,相对平均误差值在5%以内,这是可以接受的。

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