Basic Properties of Palm Oil Biodiesel Diesel Blends

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Basic properties of palm oil biodieseldiesel blends

Pedro Benjumea a,*, John Agudelo b, Andres Agudelo b

a Alternative Fuels Group, Energy Institute, Faculty of Mines, Universidad Nacional de Colombia Sede Medelln, Colombiab Group of Energy Efficient Management GIMEL, Engineering Faculty, Universidad de Antioquia, Colombia

Received 16 May 2007; received in revised form 24 October 2007; accepted 12 November 2007Available online 7 December 2007

Abstract

The basic properties of several palm oil biodieseldiesel fuel blends were measured according to the corresponding ASTM standards.In order to predict these properties, mixing rules are evaluated as a function of the volume fraction of biodiesel in the blend. Kays mixingrule is used for predicting density, heating value, three different points of the distillation curve (T10, T50 and T90), cloud point and cal-culated cetane index, while an Arrhenius mixing rule is used for viscosity. The absolute average deviations (AAD) obtained were low,demonstrating the suitability of the used mixing rules. It was found that the calculated cetane index of palm oil biodiesel obtained usingASTM D4737 is in better agreement with the reported cetane number than the one corresponding to the ASTM D976. This result is mostlikely due to the fact that the former standard takes into account the particular characteristics of the distillation curve. 2007 Elsevier Ltd. All rights reserved.

Keywords: Palm oil biodiesel; Blends; Basic properties; Mixing rules

1. Introduction

Biodiesel is currently the most widely accepted alter-native fuel for diesel engines due to its technical, envi-ronmental and strategic advantages. It has enhancedbiodegradability, reduced toxicity and improved lubricityin comparison with conventional diesel fuels. In addition,this biofuel is completely miscible with petroleum diesel,allowing the blending of these two fuels in any proportion.Biodiesel can be used neat or blended in existing dieselengines without significant modifications to the engine.However, differences in the chemical nature of biodiesel

(mixture of mono-alkyl ester of saturated and unsaturatedlong chain fatty acids) and conventional diesel fuel (mix-ture of paraffinic, naphthenic and aromatic hydrocarbons)result in differences in their basic properties, affectingengine performance and pollutant emissions. Biodiesel,produced from any vegetable oil or animal fat, generallyhas higher density, viscosity, cloud point and cetane num-

ber, and lower volatility and heating value compared tocommercial grades of diesel fuel [19].

It is important to know the basic properties of biodieseldiesel blends. Some of these properties are required asinput data for predictive and diagnostic engine combustionmodels. Additionally, it is necessary to know if the fuelresulting from the blending process meets the standardspecifications for diesel fuels. Given the difficulty of obtain-ing the basic properties of the blend by measurement, theability to calculate these properties using blending or mix-ing rules is very useful. Such an approach allows an a prioriestimation of blend properties as a function of composition

and pure component values.Clements [10] proposed blending rules for estimating thedensity, heating value, viscosity, cetane number and cloudpoint of biodiesel as a function of its methyl esters profile.By comparing predicted values with experimental data, hefound that the typical average errors were less than 2%,with the exception of viscosity, where the average errorwas 10%. Similar blending rules to those proposed by Cle-ments for calculating properties of methyl ester blends havealso been used by other researchers for estimating proper-ties of biodieseldiesel blends.

0016-2361/$ - see front matter 2007 Elsevier Ltd. All rights reserved.

doi:10.1016/j.fuel.2007.11.004

* Corresponding author. Tel.: +574 425 5319; fax: +574 234 1004.E-mail address: [email protected] (P. Benjumea).

www.fuelfirst.com

Available online at www.sciencedirect.com

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Tat and Van Gerpen [11] presented experimental datafor kinematic viscosity of a commercial soybean oil biodie-sel and its blends with grade No. 1 and No. 2 diesel fuels at75%, 50% and 20% biodiesel (by weight), from a tempera-ture close to the biodiesel melting point up to 100 C.Results showed that viscosity increased with the increase

in the percentage of biodiesel. The temperature-dependentviscosity behaviour of the blends was similar to that of neatfuels. Blend viscosities were estimated by means of a blend-ing rule, similar to the one proposed by Arrhenius anddescribed by Grunberg and Nissan [12]. The maximum dif-ferences between predicted and measured viscosities wereless than 2.05% and 3.74% of the measured values for thebiodiesel blends with No. 2 and No. 1 diesel fuels,respectively.

Tat and Van Gerpen [13] carried out a study on the den-sity of blends similar to that referenced for viscosity [11].The results indicated a linear type specific gravitytemper-ature relationship for the soybean oil biodieseldiesel

blends that was similar to that of the pure diesel fuels. Amass weighted average was used to estimate blend specificgravities. This simple approach is known in the hydrocar-bon industry as Kays mixing rule [14].

Yuan, Hansen and Zhang [15] carried out a study withdensity similar to that of Tat and Van Gerpen [13], usingthree types of biodiesel (two produced from soybean oiland another more saturated biodiesel prepared from yellowgrease). These were blended with grade No. 2 diesel fuel at75%, 50% and 25% biodiesel (by weight), and tested fromclose to the biodiesel crystallization onset temperature upto 100 C. The measurements indicated that all biodiesel

fuels and their blends with No. 2 diesel fuel had a linearspecific gravitytemperature relationship similar to purediesel fuel. The densities of the blends estimated by Kaysmixing rule showed an average absolute deviation (AAD)of less than 0.43% for all tested fuels in the temperaturerange studied.

Joshi and Pegg [16] presented experimental data fordynamic viscosity and cloud and pour points of biodieselderived from ethyl esters of fish oil and its blends withNo. 2 diesel fuel at 80%, 60%, 40% and 20% biodiesel (byvolume). The measurements of the cold flow properties ofthe blends were correlated as functions of biodiesel contentusing empirical second-order polynomials, giving regres-sion coefficients of 0.996 and 0.995 for the predicted cloudand pour points, respectively.

The present paper presents experimental density and vis-cosity data as a function of temperature, together with theheating value, distillation curves and cloud point for palmoil biodiesel and its blends with No. 2 diesel fuel. Addition-ally, the calculated cetane index of the tested neat fuels andtheir blends is obtained by empirical correlations recom-mended for hydrocarbon fuels. The aim of this work is toevaluate mixing rules for calculating the basic propertiesof palm oil biodieseldiesel fuel blends as a function of bio-diesel content (volume fraction). This approach is more

likely to be applicable to other biodiesel fuels and blends

than empirical correlations, which would be valid onlyfor the specific blends tested.

2. Methods

2.1. Blend preparation

The biodiesel used in this work was produced in a pilotplant by basic methanolysis of crude palm oil using a meth-anol/oil molar ratio of 12:1, with 0.6% sodium hydroxideby weight as the catalyst. The reaction temperature andtime were 60 C and 1 h, respectively. The methyl estercomposition of palm oil biodiesel (POB) was determinedby gas chromatography (see Table 1). The commercialgrade No. 2 diesel fuel (D) used had an elemental compo-sition by weight of 87.2% carbon, 12.8% hydrogen and0.0225% sulphur, and an aromatic content of 29.3% (13%monoaromatics, 13.3% diaromatics and 3% polyaromat-

ics). Although several blends with a wide composition spec-trum were prepared by splash blending [17], most of thetests were carried out with B5 (5% POB-95% D by volume)and B20 blends, due to their widespread use. Neat fuels aredesignated as B100 and B0, respectively. Blends were pre-pared on a volume basis at 25 C. Although blend prepara-tion on a weight basis has the advantage that weightfraction does not change with temperature, the commonpractice in the fuel industry is to carry out the mixing pro-cess on a volume basis at the ambient temperature of theblending location, usually a wholesale commercial plant.For this reason, the option selected in this work was touse blending rules as a function of volumetric fractions.

2.2. Experimental

Cloud point was measured according to ASTM D2500[18]. Density was determined following ASTM 287 [19]using calibrated glass API gravity hydrometers. A mineraloil bath with a temperature control precision of 0.02 Cwas used for measuring density at different temperatures,from close to the cloud point of POB up to 100 C. Kine-matic viscosity was determined according to ASTM D445[20] using a capillary tube viscometer. The calibration con-stant of the viscometer supplied by the manufacturer isgiven only for temperatures of 40 and 100 C, so the con-stant for all other temperatures was linearly interpolatedor extrapolated from these values. Both density and kine-

Table 1Chemical composition of palm oil biodiesel by GC

Fatty acid methyl ester Mass percent

C12:0 0.267C14:0 1.434C16:0 46.130C18:0 3.684C18:1 37.470

C18:2 11.020

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matic viscosity were measured from the cloud point of POBup to 100 C. High, or gross heating value was determinedusing an IKA automated bomb calorimeter, followingASTM D240 [21]. All fuels tested were distilled followingthe procedure established by ASTM D86 [22]. In additionto the initial and final boiling points, temperatures for dis-

tilled percentage multiples of 10 were also registered. Thetemperature values measured were normalized to standardatmospheric pressure by means of the SidneyYoung cor-relation, as recommended by ASTM D86. The calculatedcetane index for the fuels tested was determined as a func-tion of their densities and distillation curve data using theempirical correlations recommended by ASTM D976 [23]and D4737 [24].

3. Results and discussion

3.1. Basic properties of pure fuels

Experimental data on the basic properties of palm oilbiodiesel and diesel fuel are presented in Table 2. The mostcritical property of POB is its high cloud point, due to itshigh content of long chain, highly saturated methyl esters(see Table 1). At 16 C POB starts to form crystals. Ataround 12 C, these crystals may plug filters and fuel lines.These faulty cold flow properties of POB limit its utiliza-tion as a neat fuel or in rich biodiesel blends in cold cli-mates or in the winter season. POB is denser, slightlymore viscous, and has a narrower boiling interval than die-sel fuel, indicating that the fatty acid methyl esters in bio-diesel have similar boiling points. Diesel fuel, meanwhile,

is composed of a wide variety of hydrocarbons with differ-ent volatilities. This explains why biodiesel is denser thandiesel fuel despite having a lower final boiling point. POBhas a gross heating value lower than diesel fuel due tothe presence of oxygen in the methyl ester molecules. Thisdifference in heating values, expressed as energy per unitmass, is slightly reduced when it is reported as energy perunit volume, given the greater density of POB. As a resultof these differences, the calculated cetane index for POB ishigher than for diesel fuel; this agrees with the tendency

reported by several researchers for both cetane numbersand CCI [1,8,9].

3.2. Effect of temperature

In order to analyze the effect of temperature on density

and kinematic viscosity of the pure fuels and their blends,the experimental data were fitted by means of statisticalregressions.

Fig. 1 shows the effect of temperature on density (q) forpure fuels and B5 and B20 blends. In the temperature rangestudied there were no qualitative differences in the behaviorof the fuels tested. Experimental data were correlated bylinear regressions, presented in Table 3. The regressioncoefficients (R2) were always greater than 0.99, indicating,as expected, that linear regression accurately representsthe densitytemperature relationship for the fuels tested.

Viscositytemperature curves for pure fuels and severalblends are shown in Fig. 2. As can be seen in this figure,

the curves for diesel fuel and for the blends exhibit a similartrend for temperature variation, and these curves are prac-tically identical due to the small differences in the viscositiesof the pure fuels.

The variation of kinematic viscosity (g) with tempera-ture for different types of fluids has been commonly repre-sented by means of Andrade type equations, such as thefollowing [11,25]:

g eAB=TC=T2 1

The constants (A, B, C) and the regression coefficients(R2) for each regression curve shown in Fig. 2 are presented

in Table 4.

Table 2

Basic properties of No. 2 diesel fuel and palm oil biodieselProperties Units ASTM

standardDieselfuel No. 2

Palm oilBiodiesel

Density at 25 C kg/m3 D1298 853.97 864.42Mass high heating value MJ/kg D 240 45.273 39.837Volume high heating value

(25 C)MJ/m3 D240 38662 34436

Cloud point C D2500 5.0 16.0Cold filter plugging point C D6371 6.0 12.0Kinematic viscosity at 40 C mm2/s D445 4.33 4.71Initial boiling point C D86 181.5 302.2Temperature at 50% recovered C D86 284.9 326.5Final boiling point C D86 384.3 348.9Calculated cetane index D4737 46.3 57.3

D976 47.5 50.0

Fig. 1. Variation of blend density with temperature.

Table 3Linear regressions parameters for fuel densities

Fuel type Linear regression q a bT

a b R2

B100 882.6689646 0.7342772415 0.996686B20 876.6406154 0.7115968933 0.997702B5 873.0569269 0.6920565595 0.994305

B0 869.6231871 0.6792453596 0.997307

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3.3. Effect of biodiesel content

Mixing rules are used for estimating the basic propertiesof blends as a function of pure fuel properties and biodieselcontent. The suitability of these rules is evaluated by meansof the absolute average deviation (AAD), calculated as

AAD 100

NP

XNP

i1

uEXP uPRuEXP

2

where NP is the number of experimental points, u is theproperty to be predicted and the subscripts are EXP forexperimental and PR for predicted.

The GrunbergNissan mixing rule is widely used forpredicting viscosity of liquid mixtures [26]:

ln lB Xn

i

xi ln li Xn

i

Xn

j

xixjGij 3

where lB is the mean absolute viscosity of the blend, li theabsolute viscosity of pure ith component, xi and xj the molefractions of the ith and jth components, Gij the interactionparameter (Gij = 0, for i= j), and n the number ofcomponents.

When the components of a mixture have similar chemi-cal structure it is expected that they do not interact witheach other and consequently the interaction parameter inEq. (3) can be neglected. Biodieseldiesel fuel blends canbe assumed to behave this way because both liquids arenon-polar, completely miscible, and when blended their

volumes are practically additive. In this work the volumefraction and the kinematic viscosity are used instead ofthe mole fraction and absolute viscosity, respectively. With

these modifications, Eq. (3) for a binary mixture takes theform of a geometric volume average (Arrhenius-typeequation):

ln gB VPOB ln gPOB VD ln gD 4

In the above equation, V is the volume fraction and the

subscripts are B for blend, POB for biodiesel and D for die-sel fuel.

For the remaining properties, Kays mixing rule is used:

uB Xn

i

xiui 5

where uB is the property of the blend and ui is the respec-tive property of the ith component. Using volume fractioninstead of molar fraction, Eq. (5) for a binary mixture takesthe form of an arithmetic volume average:

uB VPOB uPOB VD uD 6

3.3.1. Viscosity

Fig. 3 shows the effect of biodiesel content on the viscos-ity of the blends tested for three representative tempera-tures. As can be seen in this figure, viscosity slightlyincreases with biodiesel content. The AADs obtained usingthe selected mixing rule for estimating blend viscosity were1.07%, 0.64% and 0.72% for the data corresponding to 16,40 and 100 C, respectively.

3.3.2. Density

The variation in blend density with biodiesel content is

shown in Fig. 4. As was expected, density is directly pro-portional to biodiesel content. The AADs obtained usingKays mixing rule to estimate blend densities were 0.13%,0.15% and 0.09% for the data corresponding to 16, 40and 100 C, respectively.

3.3.3. Heating value

Low heating values (LHV) were calculated from themeasured high heating values (HHV), taking into accountthe elemental composition of the pure fuels and theenthalpy of vaporization of water. As can be seen inFig. 5, the LHV of blends decreases in direct proportion

Fig. 2. Variation of blend Kinematic viscosity with temperature.

Table 4Regression parameters for viscosity

Fuel type Regression equation g eAB=TC=T2

A B C R2

B100 0.364206158 55.22818898 416.2888996 0.988622B30 0.192149860 6 0.09025836 462.560271 0.989173B20 0.162400318 6 1.85122113 491.0603185 0.962320B5 0.220089863 56.0562369 409.7122203 0.978609

B0 0.142954422 60.16294716 456.709883 0.98695 Fig. 3. Variation of blend kinematic viscosity with biodiesel content.


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to the biodiesel content. The AAD obtained using Kaysmixing rule to estimate the LHV of blends was 0.19%.

3.3.4. Cloud point

Fig. 6 shows the effect of biodiesel content on the cloud

point (TCP) of the pure fuels and on a wide spectrum ofblends. Although the mixing rule allowed an excellentmatch of the experimental points (see Fig. 6), the AADobtained was quite high (15.2%). This happened due tothe temperature scale used. Changing degrees Celsius toKelvin gives an AAD of 0.19%.

3.3.5. Distillation curve points

Fig. 7 shows the distillation curves for pure fuels and forB5, B20 and B30 blends. As can be seen in this figure, all

curves tend to intercept at a point which defines two zoneswith different behaviour. Before the interception point(approximately 80% distilled percentage), distillation tem-perature increases with distilled percentage, while after thispoint the trend is reversed. Fig. 8 shows the effect of biodie-sel content on the distillation temperatures corresponding

to three representative distilled percentages: 10%, 50%and 90%. These temperatures are designated as T10, T50and T90, and the maximum values for these are commonlyspecified in engine fuel quality standards. The ADDsobtained using Kays mixing rule to estimate T10, T50and T90 for the blends were 2.5%, 1.3% and 1.0%,respectively.

3.3.6. Calculated cetane index

The cetane number is a basic property of diesel fuels thatindicates ignition characteristics. This parameter can bemeasured in a specially designed test engine (ASTM

D613) or in a constant volume combustion apparatus(ASTM D6890) [5,9]. However, these tests are awkwardand expensive. For this reason there have been manyattempts to develop methods to estimate the cetane numberof a fuel. In order to differentiate predicted from measuredvalues, the former is called calculated cetane index (CCI),and the latter cetane number [27]. The CCI can be deter-mined using empirical correlations in accordance with theASTM D976 and D4737. Using ASTM D976, this param-eter is obtained as a function of fuel density at 15 C andthe T50 distillation curve point. ASTM D4737 additionally

Fig. 4. Variation of blend density with biodiesel content.

Fig. 5. Variation of low heating value with biodiesel content.

Fig. 6. Variation of cloud point with biodiesel content.

Fig. 7. Distillation curves of POB-D blends.

Fig. 8. Variation of distillation curve points wit biodiesel content.


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takes into account T10 and T90 values. Table 5 shows theCCI values using the two standards. Distillation curvepoints were taken according to the measured values shownin Fig. 7 and the values of density at 15 C were obtainedaccording to the linear regressions presented in Table 3.For the blends tested (B5 and B20) the effect of biodieselcontent on the CCI of the blend was not significant,and the values obtained using both methods were similar.For B100, the value of the CCI obtained using the ASTMD4737 (CCI

4737

) was higher than that obtained usingthe ASTM D976, and was in better agreement with themeasured cetane number reported for POB by MalaysianPalm Oil Board researchers [28]. The better predictionobtained using ASTM D4737 is most likely due to theinclusion of the particular characteristics of the distillationcurve.

Two approaches were used to estimate the CCI4737 ofblends (see Fig. 9). In the first, this parameter was calcu-lated from values of blend densities at 15 C and distilla-tion curve points obtained from Kays mixing rule. In thesecond case, it was estimated directly from the mixing ruleas a function of biodiesel content and the value of the

parameter for pure fuels. As can be seen in Fig. 9, theresults obtained using both approaches are similar andindicate that CCI increases with biodiesel content.

4. Conclusions

Basic properties of palm oil biodieseldiesel fuel blendswere measured according to ASTM standards.

Experimental data showing the variation of density andkinematic viscosity with temperature were properly fittedby means of statistical regressions.

According to the low values obtained for the absolute

average deviations, it was found that simple mixing rules

are suitable for predicting the basic properties of palm oilbiodieseldiesel blends as a function of biodiesel content.

The variation of distillation temperature with distilledpercentage for the tested blends is not uniform throughoutthe boiling interval: there is an interception point (approx-imately 80% distilled percentage) dividing two zones with

opposite behaviour.The ASTM D4737 produces a calculated cetane index ofpalm oil biodiesel in better agreement with the reportedcetane number than the corresponding to the ASTMD976. This result is most likely due to the fact that the for-mer standard takes into account the particular characteris-tics of the distillation curve.

Acknowledgements

The authors wish to acknowledge the financial supportof COLCIENCIAS (Instituto Colombiano para el Desarr-

ollo de la Ciencia y la Tecnologa Francisco Jose de Cal-das) to the research project 1118-06-17327. They alsoacknowledge the collaboration of ICP (Instituto Colombi-ano del Petroleo).

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Table 5Calculated cetane indexes for pure fuels and B5 and B20 blends

ASTM standard Calculated cetane index

D B5 B20 B100

D976 47.8 48.7 48.9 50.3D4737 46.6 46.9 47.0 57.7

Fig. 9. Variation of calculated cetane index with biodiesel content.


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