基于DOE方法的米糠油生物柴油混合燃料CI发动机性能分析

S. Dhingra, Rahul Raghav, Kovács András, Rohit Khargotra
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摘要

稻谷小麦是水稻处理连接的症状,含油量为10-25%,这取决于稻米品质、机械结构和其他农业气候因素。为了培养隐蔽性油的下级贮存,减少普通污染,有必要研究稻籽油作为生物柴油的用途。稻谷是一种富含油脂的农业现代产物,作为生物柴油生产的原料一直备受关注。目前的研究工作基于生物柴油米糠油对扭矩、“制动功率”、“机械效率”、“制动比油耗”、CO、CO2•HC和NO的影响,并利用RSM确定这些变量的理想值。首先,使用design Expert 6.0.8进行实验设计。以不同的废食用油(向日葵)生物柴油混合物为燃料的压缩点火发动机的性能分析。采用RSM可取性方法对参数进行优化。结果表明:发动机负载转矩为11.97 Nm,燃油掺量为2.93%时,发动机的BP值为2.03697%,ME值为36.775%,BSFC值为464.591 g/Kwh。对最佳结果进行验证后,将预测值与实际值进行比较,得出BSFC误差为5.67%,ME误差为6.72%,BP误差为5.46%,CO误差为4.86%,HC误差为4.72%,CO2误差为8.01%,NOx误差为6.14%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance Analysis of Rice Bran Oil Biodiesel Blends-Based CI ENGINE using DOE Approach
Rice wheat is a symptom of rice dealing with connection and contains 10-25% oil subject to rice quality, mechanical framework, and other Agro-climatic parts. To foster the obscuring oil subordinate stores and to lessen ordinary tainting, there is a need to research rice grain oil for use as a bio-diesel. Rice grain is an oleaginous Agro-modern build-up that has been of interest as a feedstock for biodiesel creation. The current research work based on the effect of biodiesel rice bran oil on the torque, “brake power,” “mechanical efficiency,” “break specific fuel consumption,” CO, CO2 • HC and NO, and to determine the ideal value of these variables by using RSM. First, the experimental design is prepared using Design Expert 6.0.8. To estimate the performance properties analysis of compression ignition engine fuelled with distinct blends of waste cooking oil (sunflower)biodiesel. Optimization of parameters is done by using the RSM desirability approach. The outcomes show that the optimum conditions were obtained using the desirability approach with engine load torque 11.97 Nm and fuel blends of 2.93% by volume which gives the 2.03697% BP, 36.775% ME and 464.591 g/Kwh BSFC. After the validation of optimum results, predicted and actual values were compared to find the errors, which is found to be 5.67% in BSFC, 6.72% in ME,5.46% in BP, 4.86% in CO, 4.72% HC, 8.01% CO2 and 6.14% NOx.
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