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Modeling the effects of biodiesel-diesel fuel blends on CO2 emission of a diesel engine by response surface methodology
|Caspian Journal of Environmental Sciences|
|مقاله 4، دوره 14، شماره 3، آذر 2016، صفحه 227-238 اصل مقاله (1.03 M)|
|A. Shirneshan1؛ M. Almassi2؛ B. Ghobadian3؛ Gh. Najafi3|
|1Islamic Azad University Najafabad|
|2Islamic Azad University, Tehran|
|3Tarbiat Modares University Tehran|
|Nowadays biodiesel is receiving more attention as a most important renewable energy for using in diesel engines. Inthis research, the application of Response Surface Methodology (RSM) was highlighted to investigate the effects of biodiesel-diesel blends (B0, B20, B50 and B100), engine operating parameters (engine load and speed) on CO2 emission of a diesel engine. The experiments were conducted on a four cylinder direct-injection diesel engine based on three-factor five-level central composite rotatable design. The developed mathematical models were helpful to predict the response parameters and further to identify the significant interactions between the input factors and the responses. The use of biodiesel resulted in higher emission of CO2. The results also showed that an increase in engine speed leads to an increase in the emission of CO2.On the other hand,CO2 emission is higher at low engine loads,while is lower at high engine loads.|
|Biodiesel؛ CO2 Emission؛ RSM؛ Diesel Engine|
Modeling the effects of biodiesel-diesel fuel blends on CO2 emission of a diesel engine by response surface methodology
A. Shirneshan1*, M.Almassi2, B. Ghobadian3, Gh. Najafi3
1- Department of Mechanical Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran.
2- Department of Mechanics in Farm Machinery and Agricultural Mechanization, Science and Research Branch, Islamic Azad University, Tehran, Iran.
3- Department of Mechanics in Farm Machinery, Tarbiat Modares University,Tehran, Iran
* Corresponding author’s E-mail:firstname.lastname@example.org
(Received: Nov. 10.2015 Accepted: April. 19.2016)
Nowadays biodiesel is receiving more attention as a most important renewable energy for using in diesel engines. Inthis research, the application of Response Surface Methodology (RSM) was highlighted to investigate the effects of biodiesel-diesel blends (B0, B20, B50 and B100), engine operating parameters (engine load and speed) on CO2 emission of a diesel engine. The experiments were conducted on a four cylinder direct-injection diesel engine based on three-factor five-level central composite rotatable design. The developed mathematical models were helpful to predict the response parameters and further to identify the significant interactions between the input factors and the responses. The use of biodiesel resulted in higher emission of CO2. The results also showed that an increase in engine speed leads to an increase in the emission of CO2.On the other hand,CO2 emission is higher at low engine loads,while is lower at high engine loads.
Key words:Biodiesel, CO2 Emission, RSM , Diesel Engine.
Biomass sources mostly biofuels for diesel engines are becoming increasingly important due to the growing energy needs as a consequence of spiraling demand and diminishing supply and also the environmental consequences of exhaust gases from petroleum fuelled engines(Shirneshan et al. 2014; Shirneshan et al. 2016). Besides, the requests for energy have grown very quickly due to the rapid development of certain growing economies, especially in Asia and the Middle East(Shirneshan et al. 2016). Indeed, the petroleum crisis exploded in the late 1970s and early 1980s, hence, its products became very scarce and expensive. These issues have triggered various research studies to replace the petroleum - based diesel fuel with the vegetable oils or their derivations (Canakci et al. 2009a). Biofuels such as alcohols and biodiesel have been proposed as alternatives for diesel engines (Agarwal et al. 2006; Demirbas 2007; Ribeiro et al. 2007). Biodiesel can be produced from various vegetable oils, waste cooking oils and animal fats. The fuel properties of biodiesel may be changed when different feedstocks are used. As compared to the properties of petroleum diesel fuels, biodiesel has a higher viscosity, density, pour point, flash point and cetane number, near-zero aromatic compound, and no sulfur link (Canakci et al. 2009b, Shirneshan et al. 2014). In particular, biodiesel has received wide attention as a replacement for diesel fuel because it is biodegradable, nontoxic and can significantly reduce toxic emissions and overall life cycle emission of CO2 from the engine when burned as a fuel. Biodiesel can form blends with petroleum diesel fuel at any ratio and thus have thepotential to partially, or even totally, replace diesel fuel in diesel engines(Shirneshan et al. 2014).
Biodiesel fuel has many effects on diesel engine emissions. There has been a lot of research on emission characteristics of diesel engines with biodiesel/diesel blends (Shirneshan et al. 2012; Canakci et al. 2009a). The contribution rate of traffic on CO2 emission is as high as 23%, some authors studied CO2 emission of biodiesel. In the literatures (Ozsezen et al. 2009; Utlu & Koçak, 2008; Lin & Lin 2007; Sahoo et al. 2007), it was reported that, biodiesel resulted in fewer CO2 emission than diesel after complete combustion due to the lower carbon to hydrogen ratio. The literature (Lin &Lin 2007) compared the CO2 emission between three kinds of biodiesels (from vegetable oils, animal fats and used cooking oils) and ASTM No. 2D diesel using CO2 emission index, which is defined as the CO2 emission (%) divided by the corresponding fuel consumption rate (in unit of g.h-1). Three kinds of biodiesels had lower CO2 emission indices than ASTM No. 2D diesel. This is attributed to the fact that biodiesel is a low - carbon fuel and has a lower elemental - carbon – to - hydrogen ratio than diesel fuel. But it was reported in some studies (Ulusoy et al. 2009; Ramadhas et al. 2005; Fontaras et al. 2009; Canakci 2005; Labeckas & Slavinskas 2006) that CO2 emission rise or keep similar (Song & Zhang 2008; Usta 2005),which is due to more efficient combustion. It was of course pointed out in the literatures(Labeckas & Slavinskas 2006; Sahoo et al. 2007) that in the case of biodiesel, the higher carbon dioxide emission should cause less concern because of nature recovery by raising biodiesel crops. The literatures (Carraretto et al. 2004; Lapuerta et al. 2008) evaluated the effect of biodiesel on global greenhouse gas emissions through the life cycle of CO2 emission and pointed out that biodiesel will cause 50–80% reduction in CO2 emission compared to petroleum diesel. The objective of this study is to investigate the effects of various biodiesel-diesel blends (B0, B20, B50 and B100) and engine operating parameters on changes in emission characteristics of a diesel engine. Response Surface Methodology (RSM) is employed to develop mathematical relationships between independent variables and CO2 exhaust emission as the response. In addition, using response surface plots, the interaction effects of process parameters on the responses are also analyzed and discussed.
MATERIALS AND METHODS
Biodiesel preparation and fuel properties
Since biodiesel from frying cooking oil is a more economical source of the fuel(Di et al. 2009), in the present study, biodiesel was produced from this feedstock. The source of frying cooking oil included sunflower oil and soybean oil. In the present research, biodiesel was produced by a transesterification process which was catalyzed by KOH (as Alkali catalyst) and methanol (as alcohol) in Biofuels Laboratories atTarbiat Modares University, Tehran, Iran. Then, the fuel was analyzed according to ASTM D6751 standard. The important properties of frying vegetable cooking oil and No. 2 diesel are shown in Table 1.
Test engine experimental setup and procedure
The engine tests were carried out on a 4-cylinder, four-stroke, turbocharged, water cooled and DI diesel engine (OM 314). The major specifications of the engine under the test are shown in Table 2. The diesel engine was fuelled with blends of frying vegetable cooking oil and No. 2 diesel fuel (B0, B20, B50and B100). The fuel blends were used at the different engine speeds and engine loads. In each speed test run, the maximum engine torque was reached for each fuel. The engine speed was measured by a digital tachometer with a resolution of 1 rpm. The engine was coupled to a hydraulic dynamometer to provide brake load and an AVL gas analyzer model Di Com 4000 (made by AVL Company, Austria) was used to measure CO2 emission. The engine was allowed to run for a few times until the exhaust gas temperature, the cooling water temperature, the lubricating oil temperature, as well as the CO2 gas concentration attained the steady-state values and then the data were recorded.
Experimental design and statistical analysis
The standard RSM design using Central Composite Design (CCD) was employed to examine the relationship between the response variables and set of quantitative experimental factors. The advantage of using Design of Experiments is that it provides an opportunity to study not only the individual effect of each parameter with reducing the time but also their interactions with the minimum number of experiments for achieving the optimum conditions. Hence, RSM adopts both the mathematical andstatistical techniques to describe the influence of interactions of parameters on the response when they are varied simultaneously(Montgomery 2008). The independent variables were percentage of biodiesel in fuel mixture (x1), engine speed (x2) and engine load (x3). Each independent variable had coded levels of -1, 0 and 1.The experimental designs of the coded (x) and actual (X) levels of variables are shown in Table 3. The response (Y) was CO2 exhaust emission.
The response function (Y) were related to the coded variables (xi, i = 1, 2, 3) by following second-order polynomial equation (Montgomery 2008).
The coefficients of the polynomial were represented by b0 (constant term); b1, b2and b3 (linear effects); b11, b22and b33 (quadratic effects); and b12, b13and b23 (interactioneffects):
Table 1.Properties of diesel and biodiesel fuels used for present investigation.
Table 2. Specifications of the test engine.
Fig. 1. The experimental and predicted data for CO2 emission.
Minitab software version 15.0 (Montgomery 2008) was used to develop the mathematical model and to evaluate the subsequent regression analyses and analyses of variance (ANOVA). Fig. 1shows the experimental and predicted data for CO2 emission.The developed mathematical models were effectively used to
predict the range of parameters used in the study.
Based on these models, the main and interaction effects of the process parameters on the exhaust emissions characteristics were computed and plotted in contour and surface plots as shown in Figs.2 -5.
Fig. 2(a). Contour plot of Effect of biodiesel percentage and engine speed on CO2 emission at 25% load.
Fig. 2(b). Surface plot of Effect of biodiesel percentage and engine speed on CO2 emission at 25% load.
Fig. 3(a). Contour plot of Effect of biodiesel percentage and engine speed on CO2 emission at 50% load.
Fig. 3(b). Surface plot of Effect of biodiesel percentage and engine speed on CO2 emission at 50% load.
Fig. 4(a). Contour plot of Effect of biodiesel percentage and engine speed on CO2 emission at 75% load.
Fig. 4(b). Surface plot of Effect of biodiesel percentage and engine speed on CO2 emission at 75% load.
Fig. 5(a). Contour plot of effect of biodiesel percentage and engine speed on CO2 emission at full load.
Fig. 5(b). Surface plot of effect of biodiesel percentage and engine speed on CO2 emission at full load.
RESULTS AND DISCUSSION
The experiments were performed according to design matrix (Table 3) and the experimental data for the response (CO2 exhaust emission of the diesel engine) are shown in Table 4.Table 5 summarizes the results of the dependent
variable with its coefficient of determination (R2).
The statistical analysis indicates that the proposed model was adequate, possessing no significant lack of fit and with very satisfactory values of the R2 for the response. The R2 value for CO2 emission model was 0.945 with standard error 0.41. The closer the value of R2 to unity, the better the empirical models fits the actual data. On the other hand, the smaller the value of R2, the less relevance the dependent variables in the model have in explaining the behavior of variations (Little & Hills 1978). The probability (p) values of the regression model were significant at 0.001, with no lack-of fit. The mathematical model was also inspected for its validity by comparing the experimental data and the predicted data given by the models. It can be seen in Table 4 and Fig. 2.The predicted data proved that the model provided an accurate description of the experimental data, indicating the connection between the variable and output data. This data can be also observed using visual inspection by plotting the experimental data versus the predicted data corresponding to the respective responses in the DOE software. The results demonstrated that there are tendencies in the linear regression fit, and the model explains the experimental range studied adequately. The fitted regression equation showed good fit of the models and was successful in capturing the correlation between the three preparation variables.
The results of the analysis in Table 5 showed an overall curvilinear effect on CO2 emission. As shown in Table 5, CO2 emission were linearly related to the percentage of biodiesel in fuel mixture (p < 0.05), engine load and engine speed (p < 0.001). Also the analysis showed the negative quadratic effects of percentage of biodiesel in fuel mixture and engine speed (p < 0.05) and the positive quadratic effects of engine load (p < 0.05). The interaction effect between percentage of biodiesel in fuel mixture and engine speed (p < 0.05), and the interaction effect between engine speed and engine load (p < 0.05) were significant. Other factors that contribute to the CO2 emission included the interaction effect of percentage of biodiesel in fuel mixture and engine speed and effect of percentage of biodiesel in fuel mixture and engine load were found to be not significant.
The relation between power with biodiesel percentage (x1), engine speed (x2) and load (x3) is mentioned in the following Eq. .
Figs.2 - 5show the interactions between the engine speed and responses in contour plot and surface form. The graphical form plots were obtained by holding the value of engine load at 25%, 50%, 75% and 100% constant level in each related mathematical model. The X and Y-axis values of these figures are the real values.
The predicted amounts of CO2 emission for different fuel blends and engine speeds are also shown in Figs. 3 - 6. According to the figures, the maximum amount of CO2 emission (8.2%) occurs in the rage of 2700 to 2800 rpm of engine speed at full engine load and for fuel mixture included more that 40% biodiesel. The minimum amount of CO2 emission is also less than 0.8% which found at 1000 rpm engine speed, while 25% engine load for fuel mixture included less than20% biodiesel. For the fuel blends, it is observed that the CO2 emission increase with an increase in engine speed. This increase may be due to better combustion conditions and higher atomization ratio which increase at higher engine speeds. Poor atomization and uneven distribution of small portions of fuel across the combustion chamber, along with a low gas temperature, may cause local oxygen deficiency and incomplete combustion at lower engine speeds (Fazal et al. 2011). The CO2 emission is found to increase for all fuels with increase in biodiesel percentage in fuel mixture, because of the oxygen inherently present in the biodiesel, which makes it easier to be burnt at higher temperature in the cylinder and provides a more complete combustion. Almost similar results can be found in other studies (Fazal et al. 2011;Xue et al. 2011).
Table 3. The central composite experimental design matrix.
Table 4. The experimental and predicted data for the response.
The CO2 emission continuously increases with increasing engine load. CO2 emission is primarily controlled by the local fuel-air equivalence ratio. In general, low local cylinder temperatures and lean fuel-air mixture regions at low engine loads may cause the combustion reactions to be unstable, so that CO can not continuously react into CO2 ,or a temperature is reached at which the carbon monoxide concentration appears to freeze, leading to CO formation instead of CO2 formation (Mani et al. 2009).
Under high engine loads, the molecular oxygen in biodiesel fuel improves the combustion for local rich mixtures, and the high cetane number of biodiesel fuel leads to less fuel-rich zone formation; consequently, CO reacts into CO2 and the CO2 emission increases (Tan et al. 2012).
On the other hand, the exhaust gas temperature which increases with an increase in load provides more complete combustion and more CO2 formation (Cheung et al. 2009; Tan et al. 2012; Nascimento et al. 2008;Tat et al. 2007).
Table 5. Regression coefficients, R2 and p-values of the model for CO2 Emission of the Diesel Engine.
Subscripts: 1 = Percentage of biodiesel in fuel mixture, 2 = Engine speed, 3=Engine load
* Significant at 0.05 level, ** Significant at 0.01 level, *** Significant at 0.001 level.
In this study, the mathematical models was developed using Response Surface Methodology to estimate the CO2 exhaust emission of the diesel engine. It was concluded that:
1- The Design of Experiments was highly helpful to design the experiment and the statistical analysis helped to identify the significant parameters which are most influencing on the CO2 emission.
2- The statistical models as fitted can be effectively used to predict the CO2 emission characteristics. Also the effect of biodiesel produced from frying cooking oil blends and diesel No.2 fuel on engine CO2 emission was investigated.
3- Results showed that with the increase of biodiesel in the blends, the
CO2emissionincrease due to the higher oxygen content of biodiesel that provided more complete combustion in combustion region.
4- An increase in engine speed appeared to cause an increase in the emission of CO2.
5- In general, CO2 emission is higher at high engine loads, and lower at low engine loads.These results are similar to those found in the literature and support that frying cooking oil methyl esters have similar properties with diesel fuel. Noteworthy, higher CO2 formation occurred in biodiesel employing. Therefore, research is needed to propose CO2 reduction strategies for biodiesel combustion especially in high engine loads and engine speeds. Since CO2 formation is affected by the carbon–hydrogen ratio in the fuel, one way could be reducing the fuel carbon content per unit energy to reduce CO2 emission.
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