Determination of Cetane Number from Fatty Acid Compositions and Structures of Biodiesel

Author:

Lin Cherng-YuanORCID,Wu Xin-En

Abstract

Biodiesel, which possesses the dominant advantages of low emissions and environmental friendliness, is a competitive alternative fuel to petroleum-derived diesel. The cetane number, which indicates ignition delay characteristics, is considered the most significant fuel property of biodiesel. Determining the cetane number for biodiesel by general testing equipment is time-consuming and costly; hence, a simple and convenient predictive formula for the cetane number of biodiesel is a significant task to be carried out. A reliable and convenient predictive method for determining the cetane number is proposed in this study. The key parameters for the cetane number of biodiesel were first screened out. The analysis of multiple linear regressions using the available software SPSS for statistical analysis was carried out to obtain the regression coefficients of those key parameters and intercepts to establish the predictive model. Other available experimental data verified the validity of the proposed predictive equation. The determination coefficient of the formula reaches as high as 94.7%, and the standard error is 3.486. The key parameters, including the number of carbon atoms (NC), allylic position equivalent (APE), and double-bond equivalent (DBE), were more significant for influencing the cetane number of biodiesel. In addition, the increase of NC or the decrease of either APE or DBE results in the increase of the cetane number. Moreover, the present formula is found to obtain closer cetane numbers to those experimental data and features superior prediction capability.

Funder

Ministry of Science and Technology, Taiwan

Publisher

MDPI AG

Subject

Process Chemistry and Technology,Chemical Engineering (miscellaneous),Bioengineering

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3