To Study the Influence of Injection Timing, Injector Opening Pressure and Blend Percentage on Engine Performance and Emissions by the Integration of Taguchi and RSM for an Engine Fuelled with CAOME

Q4 Energy
V. N, Y. Sujatha, Arun Kumar G L, G. B. Vaggar
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引用次数: 0

Abstract

Carbon neutral fuels must have a control over global warming. Even through passenger vehicle can be replaced with electrical and hybrid vehicles, but it is extremely difficult to replace goods transport vehicles which uses hydrocarbon fuels. Biofuels are one that can be obtained from various feedstock’s including grains and green matter with high starch and sugar content such as corn, sugar cane and sugar beets. The castor oil methyl esters, which is non-edible in nature fulfils the requirement of fuel for internal combustion engine. The conventional experimental scheme needs more time for optimization and substantial number of experiments need to perform as it is possible to vary a single operating variable at a time and is expensive. Mathematical models of Taguchi method using design of experiments (DOE) give superior results. By using DOE, Taguchi L9 orthogonal array is considered. Analysis of variance (ANOVA), The Regression Equation and signal-to-noise (S/N) ratio are obtained to predict the best parameters and to evaluate the influence of significant conditions on performance, emission and combustion characteristics. The mathematical model obtained by integration of Taguchi method and RSM is successfully validated with accuracy of 95%.
以CAOME为燃料的发动机为研究对象,采用田口和RSM相结合的方法,研究喷射正时、喷油器开孔压力和混合比例对发动机性能和排放的影响
碳中性燃料必须能控制全球变暖。即使乘用车可以被电动和混合动力汽车取代,但要取代使用碳氢化合物燃料的货物运输车辆是极其困难的。生物燃料是一种可以从各种原料中获得的原料,包括谷物和淀粉和糖含量高的绿色物质,如玉米、甘蔗和甜菜。蓖麻油甲酯是天然不可食用的,满足内燃机燃料的要求。传统的实验方案需要更多的时间进行优化,并且需要进行大量的实验,因为一次可以改变单个操作变量,并且成本昂贵。用实验设计(DOE)建立的田口法数学模型得到了较好的结果。利用DOE,考虑了田口L9正交阵列。通过方差分析(ANOVA)、回归方程(Regression Equation)和信噪比(signal-to-noise, S/N)来预测最佳参数,并评估显著工况对性能、排放和燃烧特性的影响。将田口法与RSM相结合得到的数学模型得到了验证,准确率达到95%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Mines, Metals and Fuels
Journal of Mines, Metals and Fuels Energy-Fuel Technology
CiteScore
0.20
自引率
0.00%
发文量
101
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