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用响应面法(RSM)预测和优化使用麻疯树生物柴油的 CI 发动机性能。

Prediction and optimization of CI engine performance fuelled with Calophyllum inophyllum diesel blend using response surface methodology (RSM).

机构信息

Department of Aeronautical Engineering, Hindusthan Institute of Technology, Coimbatore, 641032, India.

Government College of Technology, Thadagam Road, Coimbatore, 641013, India.

出版信息

Environ Sci Pollut Res Int. 2018 Sep;25(25):24829-24844. doi: 10.1007/s11356-018-2519-8. Epub 2018 Jun 21.

DOI:10.1007/s11356-018-2519-8
PMID:29931633
Abstract

The transportation demand in India is increasing tremendously, which arouses the energy consumption by 4.1 to 6.1% increases each year from 2010 to 2050. In addition, the private vehicle ownership keeps on increasing almost 10% per year during the last decade and reaches 213 million tons of oil consumption in 2016. Thus, this makes India the third largest importer of crude oil in the world. Because of this problem, there is a need of promoting the alternative fuels (biodiesel) which are from different feedstocks for the transportation. This alternative fuel has better emission characteristics compared to neat diesel, hence the biodiesel can be used as direct alternative for diesel and it can also be blended with diesel to get better performance. However, the effect of compression ratio, injection timing, injection pressure, composition-blend ratio and air-fuel ratio, and the shape of the cylinder may affect the performance and emission characteristics of the diesel engine. This article deals with the effect of compression ratio in the performance of the engine while using Honne oil diesel blend and also to find out the optimum compression ratio. So the experimentations are conducted using Honne oil diesel blend-fueled CI engine at variable load conditions and at constant speed operations. In order to find out the optimum compression ratio, experiments are carried out on a single-cylinder, four-stroke variable compression ratio diesel engine, and it is found that 18:1 compression ratio gives better performance than the lower compression ratios. Engine performance tests were carried out at different compression ratio values. Using experimental data, regression model was developed and the values were predicted using response surface methodology. Then the predicted values were validated with the experimental results and a maximum error percentage of 6.057 with an average percentage of error as 3.57 were obtained. The optimum numeric factors for different responses were also selected using RSM.

摘要

印度的交通需求正在大幅增长,这导致 2010 年至 2050 年期间能源消耗每年增长 4.1%至 6.1%。此外,在过去十年中,私家车拥有量每年几乎增长 10%,2016 年达到 2.13 亿吨石油消耗量。因此,这使得印度成为世界第三大原油进口国。由于这个问题,需要推广替代燃料(生物柴油),这些燃料来自不同的原料,用于交通。与纯柴油相比,这种替代燃料具有更好的排放特性,因此生物柴油可以直接替代柴油,也可以与柴油混合使用以获得更好的性能。然而,压缩比、喷射正时、喷射压力、成分混合比和空燃比以及气缸形状等因素可能会影响柴油机的性能和排放特性。本文研究了使用 Honne 油柴油混合燃料时压缩比对发动机性能的影响,并找出最佳压缩比。因此,在不同的负荷条件和恒定转速下,在单缸四冲程可变压缩比柴油机上进行了试验。为了找出最佳压缩比,在一台单缸四冲程可变压缩比柴油机上进行了试验,结果表明 18:1 的压缩比比低压缩比具有更好的性能。在不同的压缩比下进行了发动机性能试验。利用实验数据,建立了回归模型,并利用响应面法对其进行了预测。然后,将预测值与实验结果进行了验证,得到了最大误差百分比为 6.057%,平均误差百分比为 3.57%。还使用 RSM 选择了不同响应的最佳数值因素。

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本文引用的文献

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Environ Sci Pollut Res Int. 2018 Apr;25(10):9523-9538. doi: 10.1007/s11356-018-1241-x. Epub 2018 Jan 21.
2
Process optimization for biodiesel production from mahua (Madhuca indica) oil using response surface methodology.采用响应面法对麻疯树(Madhuca indica)油生产生物柴油的工艺进行优化。
Bioresour Technol. 2006 Feb;97(3):379-84. doi: 10.1016/j.biortech.2005.03.014.
Experimental assessment and multi-response optimization of diesel engine performance and emission characteristics fuelled with Aegle marmelos seed cake pyrolysis oil-diesel blends using Grey relational analysis coupled principal component analysis.
使用灰色关联分析与主成分分析相结合的方法,对以麻疯树籽饼热解油-柴油混合物为燃料的柴油机性能和排放特性进行实验评估和多响应优化。
Environ Sci Pollut Res Int. 2019 Mar;26(7):6980-7004. doi: 10.1007/s11356-019-04164-8. Epub 2019 Jan 15.
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Multi-objective optimization of diesel engine performance and emissions fueled with diesel-biodiesel-fusel oil blends using response surface method.使用响应面法对柴油-生物柴油-航空煤油混合燃料的柴油机性能和排放进行多目标优化。
Environ Sci Pollut Res Int. 2018 Dec;25(35):35429-35439. doi: 10.1007/s11356-018-3459-z. Epub 2018 Oct 22.