Cold flow properties: Applying exploratory analyses and assessing predictive methods for biodiesel and diesel-biodiesel blends

被引:7
作者
Santos, Shella M. [1 ]
Wolf-Maciel, Maria R. [1 ]
Fregolente, Leonardo, V [1 ]
机构
[1] Univ Estadual Campinas, Sch Chem Engn, Campinas, Brazil
关键词
Cloud Point; Pour Point; Cold Filter Plugging Point; Principal Component Analysis; Hierarchical Cluster Analysis; HIERARCHICAL CLUSTER-ANALYSIS; LOW-TEMPERATURE PROPERTIES; FATTY-ACID-COMPOSITION; COMPONENT ANALYSIS PCA; OIL METHYL-ESTERS; FUEL PROPERTIES; PHYSICOCHEMICAL PROPERTIES; KINEMATIC VISCOSITY; OXIDATIVE STABILITY; ALKYL ESTERS;
D O I
10.1016/j.seta.2023.103220
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
With the necessity to mitigate climate change, fossil fuels have been replaced by biofuels. Currently, biodiesel, which is basically a mixture of esters used with diesel as a blend, is the most popular biofuel. As an advantage, biodiesel has lower and less harmful pollutant emissions compared to diesel, besides being renewable and biodegradable. However, its applicability at low temperatures requires caution due to crystallization. To measure biodiesel operability at low temperatures, cold flow properties (CFPs) such as cloud point (CP), pour point (PP), and cold filter plugging point (CFPP) are monitored. CFPs can be calculated based on physical properties or ester composition. Therefore, exploratory analyses were applied to investigate the influence of some esters on CFPs to develop new predictive methods with relevant esters. Also, existing methods that predict CFPs were assessed and their accuracy was compared by using the parameter Average Absolute Deviation (AAD). The accuracy of CFPs prediction was highly dependent on the biodiesel type and the suitable method. The most precise method for CP, PP, and CFPP prediction achieved AAD = 1.34 %, 1.22 %, and 1.16 %, respectively. For biodiesel-diesel blends new methods for CFP's prediction were developed with AAD inferior to 1 %, similar to existing methods.
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页数:19
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