Skip to main content
ARS Home » Midwest Area » Peoria, Illinois » National Center for Agricultural Utilization Research » Bio-oils Research » Research » Publications at this Location » Publication #368100

Research Project: Value-added Bio-oil Products and Processes

Location: Bio-oils Research

Title: Correlating the cold filter plugging point to concentration and melting properties of fatty acid methyl ester (biodiesel) admixtures

Author
item Dunn, Robert

Submitted to: Energy and Fuels
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/5/2019
Publication Date: 12/5/2019
Citation: Dunn, R.O. 2020. Correlating the cold filter plugging point to concentration and melting properties of fatty acid methyl ester (biodiesel) admixtures. Energy and Fuels. 34(1):501-515. https://doi.org/10.1021/acs.energyfuels.9b03311.
DOI: https://doi.org/10.1021/acs.energyfuels.9b03311

Interpretive Summary: Mathematical equations were developed to accurately predict the low-temperature operability of complex mixtures of fatty acid methyl esters (FAME). FAME made from agricultural sources (plant oils) can be used as alternative fuels for compression-ignition (diesel) engines (biodiesel) as well as lubricants, metal working fluids, cleaners, plasticizers, polymers, coatings, ink solvents, paint strippers and varnish and graffiti removers. Fuel systems in diesel-powered vehicles require the fuels to maintain fluidity to inject them into the combustion chambers and operate the engines. Accurate mathematical models can predict the temperatures where startup and operability of diesel-fueled engines will be compromised during cold weather. This research yielded three models that calculate limiting temperatures for diesel-fueled engines based on the composition and properties of complex mixtures of the FAME. These new models were more accurate than existing correlations. Results from this research will 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, waste cooking greases, and animal fats. Its most common form is fatty acid methyl esters (FAME) from transesterification of lipids and methanol. Biodiesel has physical properties that compare well with conventional diesel fuel (petrodiesel). However, biodiesel has poor cold flow properties that must be monitored in cold weather. In this work, three correlation models are introduced that accurately calculate the cold filter plugging point (CFPP) of biodiesel. The models were developed using measured CFPP data from neat (unblended) biodiesel fuels and 24 binary biodiesel admixtures. The biodiesel fuels studied were from canola, palm, and soybean oils and yellow grease (CaME, PME, SME and YGME). The solid-liquid equilibrium (SLE) model required accurate concentration, melting point (MP), and enthalpy of fusion ('H[fus]) data for each FAME species in the mixture. These data were used to infer the SLE phase transition temperature (T[SLE]) of the biodiesel mixtures. The T[SLE] demonstrated a linear correlation (R² = 0.977) with CFPP. The MODified Empirical Correlation (MODEC) model (R² = 0.980) was obtained by analysis of 1/(CFPP) versus ln(y[C16]) data where y[C16] is the mass fraction of methyl palmitate (MeC16). Finally, a second-order polynomial (R² = 0.982) was derived to calculate the CFPP from the modified long-chain saturation factor (LCSF[mod]), which was defined as a weighted average mass fraction of C16+ saturated-FAME (SFAME) in the mixtures. Weight factors were the MP of the corresponding SFAME species. Prevalidation tests on these models yielded good results for the calculated CFPP data. These performances exceeded those obtained by using 26 models from the scientific literature. The MODEC model performed better by a small margin than the other two new models. The main benefit of the MODEC model is that it requires just the yC16 value instead of the complete compositional analyses needed to apply the SLE or LCSF[mod] models.