Understanding the thermophysical behavior of biodiesel-based synthetic fuels through experimental data and models

Abstract

The development of synthetic fuels is one of the most interesting research alternatives to reduce the energetic dependence of our society on fossil fuels as long as renewable raw materials are used to produce them. In the last years, biofuels, involving bioalcohols and biodiesel, have been proven to be efficient alternatives to mineral fuels. However, these fuels have some deficiencies, mainly related to their calorific power, since they are in a more oxidized form. The use of mixtures of fuels from different sources (minerals and biofuels), known as blends, allows to obtain a trade-off solution among performance and sustainability. The success of this option is evidenced in the generalized deployment of the diesel-biodiesel blends in all fuel’s distribution networks across the European Union. Nevertheless, it is possible to design new fuels with enhanced features by finding the best composition that yields the optimal fuel properties. To this end, it is important to understand the behavior of these solutions by complementing experimental data with predictive tools to estimate the physicochemical properties of these systems and select the most suitable fuel formulations. This work is a theoretical-experimental contribution to the aforementioned topic. On the one hand, a property database of a set of dissolutions that can affect the combustion performance is provided. A study is proposed for ternary systems comprising hexane, two alcohols (methanol, ethanol), and fatty acid methyl esters (FAMEs). For each of these systems, volumetric properties and mixing energies and viscosities are presented. Obtained results support the discussion on the structural configuration of these solutions. The experimental information will be modeled using a multiproperty approach with our own model [1]. In addition, two predictive models, COSMO-RS [2] and UNIFAC [3] are used to complement the interpretation of the systems, and also check their predictive capacity. On the other hand, ternary systems are estimated with EoS/gE model based on SRK equation and using one of the former predictive models, as a mixing rule, to modify the dispersive term [1]. The discussion will be addressed in order to establish the best formalism that can be used for the optimal detection of synthetic fuel.