Location: Bio-oils ResearchTitle: Correlating the cloud point of biodiesel to the concentration and melting properties of the component fatty acid methyl esters
Submitted to: Energy and Fuels
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/11/2017
Publication Date: 12/11/2017
Citation: Dunn, R.O. 2018. Correlating the cloud point of biodiesel to the concentration and melting properties of the component fatty acid methyl esters. Energy and Fuels. 32(1):455-464. https://doi.10.1021/acs.energyfuels.7b02935.
Interpretive Summary: Mathematical equations were developed to accurately predict the cold flow properties of complex mixtures of fatty acid methyl esters (FAME). FAME made from agricultural sources (plant oils) have many productive uses including as alternative fuels (biodiesel), lubricants, metal working fluids, cleaners, plasticizers, polymers, coatings, ink solvents, paint strippers and varnish and graffiti removers. The design of processing equipment depends on mathematical models in accurately determining the temperatures where FAME mixtures begin to gel and form solids. This research yielded two models that can calculate gel temperatures based on the chemical compositions and properties of complex mixtures of FAME more accurately than existing correlations. Results from this research will directly benefit industry, fuel producers, terminal operators and users that need to process, store and handle biodiesel during cool weather in moderate temperature climates.
Technical Abstract: Biodiesel is a renewable alternative diesel fuel made from plant oils and animal fats. In the form of fatty acid methyl esters (FAMEs), it is usually obtained by transesterification of plant oil or animal fat with methanol in the presence of catalyst. Most of the fuel properties of biodiesel compare well with conventional diesel fuel (petrodiesel). One major disadvantage of biodiesel is its relatively poor cold flow properties which must be monitored during cold weather in moderate temperature climates. Two correlation models were developed to accurately calculate the cloud point (CP) of biodiesel. Both models were developed using measured CP data from binary admixtures of biodiesel fuels made from canola, palm, and soybean oils and yellow grease (CaME, PME, SME, and YGME). One model was based on solid-liquid equilibrium (SLE) thermodynamics in organic mixtures. This model required fatty acid concentrations (FA profile) and melting point (MP) and enthalphy of fusion ('Hfus) data for each FAME species in the mixture. A high degree of correlation (R² = 0.949) was found between CP and the calculated mixture SLE transition temperature (TSLE). Regression analysis yielded an equation for calculating the CP of FAME mixtures. The modified empirical correlation (MODEC) model (R2 = 0.949) was derived from 1/CP versus ln(yC16) data where yC16 is the mass fraction of methyl palmitate (MeC16)] in the mixture. The performances of both models in predicting the CP of multicomponent FAME mixtures (biodiesel) were compared against results from six empirical correlation models from the literature. The SLE model performed best by having close to a 1:1 correlation between calculated (CP-cal) and measured CP data and the highest accuracy with respect to average deviations. Although the MODEC model did not exhibit a 1:1 correlation, it performed nearly as well as the SLE model in accurately calculating the CP of biodiesel. The main benefit of the MODEC model is that it requires only a measured yC16 value vis-a'-vis complete analysis of the FA profile in order to apply the SLE model.