Model for Predicting the Cloud Point of Biodiesels

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The use of biodiesel fuels is limited in cold climates by its tendency to crystallize, which blocks filters, clogs tanks, and generally restricts flow. The crystallization properties of biodiesel are directly related to the chemical composition of the fuel, which is not regulated. Since biodiesel fuels can be made from any fat source, the cloud point (onset of crystallization temperature) varies significantly. The cloud point of biodiesel fuels is a complex, non-linear function of composition of fatty acid methyl ester composition, making it difficult to predict. Currently, models for predicting the cloud point are based on statistical methods, which are based on data and measurements. These models are limited because they can only predict the behavior for those specific compositions.

Purdue University researchers have developed a model that can accurately predict the cloud point of the mixture of fatty acid methyl esters according to their chemical composition. Since this model is not based on data or statistical methods, it clearly predicts the non-linear behavior of methyl ester mixtures.

Advantages:
-Not based on statistical methods, so it accurately predicts the cloud point of fatty acid mixtures
-Predicts the cloud point of a mixture of biodiesel and petroleum diesel once chemical composition is known

Potential Applications:
-Biofuel Manufacturers
Aug 3, 2012
Utility Patent
United States
9,026,421
May 5, 2015

Aug 3, 2011
Provisional-Patent
United States
(None)
(None)
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