Improving the Properties and Engine Performance of DieselâMethanol

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Improving the properties and engine performance of Diesel-Methanol-nano particles blend fuels via optimization of the emissions and engine performance Sina Khorramshokouh, Vahid Pirouzfar, Yasaman Kazerouni, Ahmad Fayyazbakhsh, and Reza Abedini Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.6b01856 • Publication Date (Web): 19 Aug 2016 Downloaded from http://pubs.acs.org on September 5, 2016

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Improving the properties and engine performance of Diesel-Methanol-nano particles blend fuels via optimization of the emissions and engine performance Sina Khorramshokouha, Vahid Pirouzfarb*, Yasaman Kazerounia, Ahmad Fayyazbakhsha, Reza Abedinic

a

b

Department of Chemical Engineering, Islamic Azad University, Central Tehran Branch, Tehran

Young Researchers and Elite Club, Central Tehran Branch, Islamic Azad University, Tehran, Iran c

Faculty of Chemical Engineering, Babol Noshirvani University of Technology, Babol, Iran

Abstract The present paper tries to investigate the fundamental aspects of air pollutant, fuel properties and engine performance during transient operation of naturally aspirated and turbocharged diesel engines in addition to comparing them with new experimental results using methanol as an oxygenate additive. The additives that can reduce the soot emission are various oxygenate alcohols (Methanol, Ethanol and n-Butanol). The additives which are used for improvement of the fuel properties (Cetane number enhancers) are tertiary additives. Meanwhile, the additives used for increasing the engine performance are nano metallic additives such as, Silica, Alumina, Cerium and Manganese. This research demonstrates the effect of various additives on performance of diesel engine, emission and diesel fuel properties by different models, in order to address the optimum and best condition. This paper shows the effect of different oxygenate additives on reduction of the soot formation, though this effect was different in the different models adopted. This research also illustrates the effects of tertiary additives and nano metallic additives on the fuel properties and engine performance, respectively,

*

Corresponding author: V.Pirouzfar; Tel: +98 912 2436110. E-mail address: [email protected]).

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owing to type of the additives (additive name). Moreover, this paper examined the effect of other conditions (engine load, engine speed and injection timing) on the above mentioned responses.

Key words: Blend diesel fuel modeling, Air pollutant, Nano metallic additives, Tertiary additives, Engine performance.

1. Introduction Diesel engines are commonly employed in transportation systems thanks and construction machines to their extraordinary fuel properties and efficiency [1-5]. Diesel is a fossil fuel base that mostly consists of aliphatic hydrocarbons with 8 to 28 atoms, while boiling points are differing from about 130 to 380 ˚C [2,3]. The exhaust emissions from the diesel engines are providing many genres of air pollutants and exhaust emissions such as, nitrogen oxides (NOx), particulate matter (PM), unburned total hydrocarbon (UTHC) and carbon monoxide (CO). The environmental solicitude of climate revolution, global warming and increase of fossil fuels (especially diesel) have greatly enhanced the benefits for application of renewable fuels in the internal combustion engines. Recently, depletion of the fossil fuel resources due to significant volume of continuous usage has attracted the attention of persons in all over the world whose lives rely on this heat energy resource in all aspects. The main source of greenhouse gas emissions are the fossil fuels [6-8]. Increasing of the environment pollutants has triggered exploration for an alternative and new source of energy. For emission release restrictions, investigators have focused on two types of engine performance or fuel modifications techniques. Therefore, improvement of the fuel combustion contributed to use of reasonable prices, significant efficiency and renewable fuels [7-10]. Alcohols as oxygenate additives can be applied together with the diesel for the engines to reduce the air pollutants and emissions and enhance or the performance of diesel engines [11-13]. These additives can be used as high performance oxygenate materials due to short molecular chain, large amounts of oxygen in their structure and low molecular


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weight of alcohols in comparison with the diesel fuel. All these reasons can contribute to modify the combustion of diesel fuel and to consequently reduce the emissions [14-19]. Many types of these oxygenate materials with various chemical forms, such as methanol [20-22], ethanol [23-26], and nButanol [27-29] have been examined to possess their high performance properties as additives. For using the alcohols in the diesel engines, different techniques were explained such as blending [30,31], emulsification [32,33], fumigation [34-36], and dual ignition [37]. The fault of dissolving alcohols in the diesel fuel and stability of the fuel blends are affected thorough water impurity in these alcohols, temperature, and lower ambient temperature. On the other hand, based on previous study, ethanol has a low Cetane index, which cause a lower Cetane Index of blended fuel derived from ethanol and diesel that makes auto-ignition difficulty and provides delay of long ignition [1]. In the previous studies, it was fairly complex to reach high quality of ethanol-diesel by direct injection, but today this concern may be solved by mixing tertiary additives (i.e. nitro methane (NM), nitro ethane, methyl ester, 2-methoxy ethyl ether (MXEE), etc.) in alcohols-diesel blends [38-41]. Moreover in the previous studies, it was observed that blending of alcohols into the diesel leads to reduction of the engine performance, but today this concern may be resolved via nano metallic additives [1, 41]. Methanol is an appropriate candidate as employed additive in blended fuel combustion at internal engines and other types of engines, either blended with diesel or gasoline. In the United States, the methanol has expected less consideration in comparison with the ethanol as a substitute to the fossil fuels. This is because the support of based corn ethanol provided certain political benefits in the 2000s [42]. Methanol is also known as methyl hydrate, wood spirits, wood naphtha, methyl alcohol, or wood alcohol, with chemical formula of CH3OH. Methanol has been given the name of wood alcohol since it was once produced specially as a destructive distillation byproduct of the wood. Today, the industrial methanol is produced in a catalytic process straightly from carbon dioxide , hydrogen, and carbon monoxide. In the previous studies, there are three general usage of methanol in diesel engines direct blend [4345], straight (direct) injection [46] and port injection [47,48]. Like ethanol, methanol has a high octane number, flammability limit, oxygen ratio and low carbon to hydrogen ratio [49]. Moreover, methanol and ethanol have higher vaporization heat than diesel fuel


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that cools the air entering into the diesel engine and improve the efficiency (volumetric) and power output [50,51]. Moreover, they have some negative impacts for example in cold starting, and a lower latent heating [51,52]. Therefore, methanol has a lower flash point than diesel, which is known as high volatility and a disadvantage for fuel storage and combustion safety. However, for solving the lubrication problem, a lubricant additive (like nitro methane, nitro ethane, etc.) should be blended with the fuel to improve its lubrication properties [1,53-55]. The main diesel properties (for example flash point and Cetane number) changed with blending the alcohols. Since the alcohols have different properties from the diesel fuel and these differences are rather significant in some conditions. For improving the Cetane Number (CN) and modifying the other properties, and also for prevention of phase separation and solving the stability problem of fuel, the tertiary additives shall be used [1-4, 3841]. Gerdes and Suppes reported that aromatic matter of the diesel can affect the ethanol solubility in the diesel and the efficiency of emulsifiers. Reducing the aromatic of the diesel will affect the ethanol miscibility in the diesel and will influence the additive amount needed to attain a homogeneous blend [56]. Modeling of diesel fuel engine by various methods aims at obtaining the optimization points and the best conditions. This research addressed the impact of various models on the diesel fuel and compared these models. Many studies, researched various variables that affected the engine performance, exhaust emission and fuel properties of the diesel fuel. There are many variables that influenced combustion performance of the diesel fuel. The main important variable is the oxygenate additive. With blending of the oxygenate additives with the diesel fuel, oxygen amount of the diesel increases. Oxygen content of the neat diesel is zero. So with increasing of the alcohol as an oxygenate additives, the oxygen content of the fuel increases. This increase can aid the combustion to be completed. The second type of additives are the tertiary additives (CN improver). These additives have two duties. The first duty is improving the CN and the other chemio-physical properties. The second duty of CN improvers is to promote the fuel stability (stability of the fuel could decrease by blending with oxygenate fuel). Another additive that effected the combustion performance is the nano metallic additive. The main duty of this additive is increasing of the engine performance. The goal of this


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piece of work is to review the literature regarding the influence of different alcohols and tertiary additives on emissions, performance of diesel engine and combustion of diesel, and to compare the obtained results with those of new experiments using methanol as an oxygenate additive. Other goal of this research is to find the effect of some additives especially methanol on exhaust emission and to find the optimization condition. The main reasons for using the oxygenate fuel in the diesel engine are: higher oxygen content of alcohol as compared to diesel fuel (oxygen content of neat diesel engine is zero), smaller molecular weight and shorter molecular chain length than diesel fuel. This experimental study showed that using Methanol as an oxygenate additive for reduction of the soot emissions outperforms using ethanol and n-butanol, but it is properly potential to increase the contents of nitrogen and carbon oxides. Oxygen content of methanol is higher than other alcohols, so it can propel the combustion process to complete, and leads to reduce of soot emission and increase of brake specific fuel consumption (BSFC). In this experimental study methanol was used with 7% content in the blend, MXEE and NM as the tertiary additives (CN improver) and used a type of silica and manganese as nano metallic additive. The experiments were performed in different engine speeds and loads. Moreover, at the end of this research optimal conditions are taken into account for all the major variables and parameters.

2. Experimental and methods 2.1. Experimental and laboratory equipment The tests were performed on a diesel engine with 4 cylinders, turbocharged, water cooled, DI engine (MT4.244), had 3.99-L displacement and with a peak power output of 61.5 kW at 2200 rpm. The methanol applied in these experiments was essentially limited to anhydrous methanol because the hydrous methanol were insoluble in majority of the diesel fuels. Analysis-grade anhydrous methanol with purity 99.8 wt. % and commercial diesel fuel were used. Two different tertiary additives having high CN (MXEE and NM) were blended with two various Nano particle additives (Manganese and a type of silica) in methanol-diesel fuel. Table 1 is presented specification of the AVL 465 analyzer (for measure CO, HC and soot emissions). Table 2 is summarized specification of the MRU 1600-L (for measure the NOx emission). The physico-chemical properties of methanol, ethanol, n-butanol and


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diesel are shown in Table 3. Photo of dynamometer coupled with diesel engine in test cell shown in Figure 1.

2.2. Statistical analysis procedure and experimental design The variables of factorial design via actual and coded levels are summarized in Table 4. The effects of Methanol-diesel-tertiary additive-Nano metal additive blends on fuel properties, exhaust emissions and engine performance were experimented in various conditions. In this research, tests were performed in two level for percentage of engine load and speed, Methanol percentage and Nano-metal or particles additives. Factorial is known as an appropriate statistical way for exploiting and improving the models and experimental design, finding optimum conditions, and contributes to identification of the effect of multiple variables for desired purpose. The detailed statistical procedure and model development technique are reported elsewhere [1,41]. In this study, type of tertiary additive (X1), class of Nano-metal additives (X2), load percentage (X3) and speed of engine (X4) were selected, also exhaust emissions (soot, HC, NOX), performance of disel

engine (Power, BSFC) and diesel properties (i.e. viscosity and CN) were taken as responses of the function. The type of tertiary additive and class of Nano-particle is dimensionless and categorical and another variables (load percentage and engine speed) are numerical. The Design Expert statistical software (Version 7.0, 2005; Minneapolis, MN, USA) was employed for both calculation of the coefficients of equation and regression analysis of the data. Authorized investigation was also executed to prophesy shape of the curve and 3D graph produced by the model. The developed and optimized polynomial model was employed based on the validation procedure and terms such as significant value (p < 0.05), coefficient of variation (CV), coefficient of multiple correlation (R2), adjusted multiple correlation factor (adjusted R2) and the least remarkable lack of fit provided by Design-Expert®. The multiple correlation (R2) coefficient distributes the standard coefficient of correlation. It is applied in multiple regression analysis to distinguish the quality of the divination of the dependent variable. It is due to the squared correlation between the actual values and the predicted of the dependent variable. In statics method and probability, the coefficient of


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variation (CV), also known as relative standard deviation, is a standardized measure of scattering of a probability distribution or frequency distribution.

2.3. Fuel specifications Fuel specification involves some of the main properties such as, chemical and physical properties, engine performance (that gets affected from fuel) and exhaust emissions. In this research we have studied viscosity and CN as fuel properties. The viscosity of a fluid is a measurement of its resistance to piecemeal deformation by shear or tensile stress. For liquids, it liaises the informal sense of thickness. For example, viscosity of honey is higher than water. CN is an index of the diesel fuel combustion speed. It is a reverse of the similar octane rating for gasoline. The CN is the main factor in determining the diesel fuel quality, but not the only one; other measurements of diesels quality include lubricity, sulfur content, energy content, density properties and cold-flow. The BSFC is defined to the break power ratio. BSFC is impacted by following factors: 1) useful output power, 2) volume of additive, and 3) engine speed. Engine power or horsepower is the maximum power that an engine can put out. In this research, the effect of different additives on HC, NOX and soot formation as exhaust emissions were studied. HC (hydrocarbons) are very toxins. Hydrocarbons are a maximum contributor to smog, which can be a main problem in urban areas. And could be the main problem for human health, because can cause to increase of cancer. The main material for created the soot emission is PAH (Polyaromatic

Hydrocarbons).

Polyaromatic

Hydrocarbons

are hydrocarbons—organic

compounds providing only carbon and hydrogen—that are composed of multiple aromatic rings that is very toxic for human health.

4. Result and Discussion 4.1. Emissions 4.1.1. HC&CO Emissions CO emission is very poisonous and must be reduced as much as possible. It is produced either directly or indirectly by combustion of fuels. In an ideal combustion, oxygen (O2) and carbon (C) combine


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together to produce CO2. However, the formation of CO2 takes place when the O2 available during combustion is inadequate to form CO2. All of the previous studies [57-66] have noticed an increase in the CO emission with blending of alcohol to diesel. The reason for this observation is that the oxygen amount needed to produce CO increases with blending of the alcohols. Higher content of alcohols mixtures can result in higher emission of carbon monoxide in greater engine load at limited extent due to lower combustion temperature caused by significant latent heat of vaporization that alcohols have. At a greater compression ratio and higher load, the temperature of combustion goes higher. This results in higher affinity of oxygen with carbon. The influence of oxygen atom in alcohol oxidation reaction will be increased. Due to this condition, carbon monoxide is converted into carbon dioxide and the CO formation decreases. This study concentrated specifically on HC exhaust emissions. It is expected that CO and HC follow the same trend because they are caused by the same physical phenomenon. Table 5 lists the experimental data where methanol was applied as an oxygenate additive. In this table, it is clear that methanol has a low negative effect on HC. This can be owing to the minimal droplet size pre

requisite for the micro explosion of the diesel-methanol

blend which leads to the droplets require a longer time for nebulization before evaporation occurs, and so higher boiling temperature. Effect of CN improver additives on HC emission is negative. However, the effect of Nitro methane on reduction of HC was lower than MXEE. At the end, the nano metallic additives could increase the HC emissions and Table 5 showed that the effect of silica is greater than that of Manganese. The normal probability for the HC models are illustrated in Figure 2. This figure demonstrates an acceptable agreement between the experimental data and the model data for the HC emission.

4.1.2. NOX Emission In the combustion theory, there are three different mechanisms in formation of the nitrogen oxides. They are 1) thermal formation of nitrogen oxides that shown by Zeldovich mechanism, 2) prompt formation of nitrogen oxides shown by Fenimore mechanism and, 3) nitrogen oxides formation owing to nitrogen existing in the fuel itself. The prompt and thermal formation of the nitrogen oxides occur


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when there is an increase in the oxygenate fuel and compression ratio. The reactions under Zeldovich mechanism as given below [1,41]: N2 +

O

NO +

N

(1)

N +

O2

NO

+

O

(2)

N +

OH

NO

+ H

(3)

Three reaction of Zeldovich mechanism are reversible. The relations of Zeldovich was the first to offer the impact of the first two reactions [1]. The centralization of oxygen in diesel-rich combustion is low, so second reaction has lower significance than in diesel-lean combustion reaction with the hydroxyl radical in the end go the major sink for N. In Fenimore mechanism, the reactions are described differently: CH

+ N2

HCN

+ N

(4)

HCN

+ O

NCO

+ H

(5)

NCO

+

H

NH + CO

(6)

H

H2

(7)

H

(8)

NH N

+ +

OH

NO +

If the nitrogen content of the fuel is high, then the nitrogen-containing compounds are oxidized and become a potential source of NOX which is also called fuel nitrogen oxides. The formation of Nitrogen oxides is quite complex because numerous intermediate types are there and several hundred reversible reactions take place with the real rate constant values being still unknown. It has been earlier research reported that the presence of diesel-born oxygen could increase the nitrogen oxide pollutions. The O2 that is in the diesel could give rise to the NO formation and decrease the losses of heat through the soot radiation subsequent in higher in-cylinder combustion temperature. Table 5 shows the experimental data where methanol is applied as an oxygenate additive. In this table, it is noticeable that the methanol has a positive impact on the emission of NOX. Before adding the oxygenate additives to diesel fuel, oxygen content of the diesel was zero. When oxygenate additive was employed (methanol) oxygen content of the diesel increased, however required oxygen to produce the nitrogen oxides prepared. Oxygen of the fuel in the hotspot of exhaust reacted with


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nitrogen of air and produced the nitrogen oxides. The 3D response plots from the combined effects of X3 (engine load) and X4 (engine speed) on (a) NOX are illustrated in Figure 3. This figure revealed a positive effect of engine load on NOX and a negative effect of engine speed on this emission. The load engine effect on NOX is greater than the other responses. The normal probability figure for NOX emission showed that the experiments data are properly consistent with those of NOX emission models.

4.1.3. Smoke Emission The oxygenated fuels are known to reduce the smoke emissions. Combination of the particle materials changes with fuel quality, combustion conditions and engine technology. Size of the particle is very important, because the smaller particle size, the more dangerous will be the issue. Smoke emission is an analytic of the dry soot formations as one of key compounds of particulate components and matter. Increasing of alcohol content - especially methanol - causes a high reduction in smoke emission. Increasing of the alcohols could affect on reduction of smoke emission because raising oxygen content causes completing the combustion. On the other hand, methanol had a lower molecular weight and lower molecular chain and network in comparison to pure diesel that leads to a lower amount of smoke emission. The lower smoke emission can be illustrated since the presence of the fuel O2 decreases the possibility of local soot emission (higher local ratio of fuel/air) that is oxidized during the diesel fuel combustion. Therefore, it must be tried to reduce spreading of the diesel engine exhaust, because this is the most dangerous part of the output soot in the diesel engines. Furthermore, it could be find out that the key factor in dangerous features of the exhaust emission is PAH (poly aromatic hydrocarbons) which is itself the main reason for the soot formation. Applying the alcoholdiesel fuel in organic form was of a little importance to add emission of OH radicals and inert H2O2. In this study (Table 5) that used methanol as a oxygenate additive, the effect of methanol on increasing of the soot emission was really significant, although the tertiary additives like methanol can limit the soot emission (especially Nitro Methane). The influences of tertiary additives on reduction of the soot emission is larger than HC emission. The 3D plots from the combined impacts and effects of X3 and X4 on the Soot emission are shown in Figure 3. In this figure, it is evident that the load of


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engine has a considerably positive impact on the soot emission but the speed of engine has a negative impact.

4.2. Engine Performance When the oxygenate fuels are blended to the diesel fuel, the BSFC is enhanced because addition of the oxygenate fuels for the diesel leads to increasing of the O2 percent in the novel and modified fuel that contributes to a complete ignition. All of alcohols have a positive effect on the BSFC. However, the influences of methanol on BSFC is higher than butanol and ethanol. This effect may be ascribed to the higher O2 content of methanol than ethanol. The engine power is the main and most effective factor in selection of the correct additive. Adding methanol to the diesel fuel leads to increasing of BSFC, but at the meantime degrades the engine power (as shown in Table 5). Table 5 demonstrates a better effect of silica on increasing of BSFC and engine power as compared to that of manganese. In this table, the greater effect of MXEE than NM on reduction of engine performance is evident. The 3D response plots from the combined effects of load and speed of engine on the BSFC and Power are illustrated in Figure 3. These figures showed that increasing of engine speed improves the engine performance. Moreover, these figures showed that increasing of the engine load gives rise to the engine power, but resulted in a greater reduction in BSFC. However, the estimated BSFC and power models versus experimental data (actual results) attained at optimum conditions are shown in Figure 4. These figures proved an acceptable agreement between the experimental results and the model data. Table 5 and Figure 3 clearly showed that increasing of speed of engine causes a negative impact on all of the air pollutants, while having a positive impact on the engine power and BSFC.

4.3. Fuel Properties The CN and flash point as effective properties of diesel have changed by blending with the alcohols. This is because the alcohols have various properties from the diesel fuel and these differences are very large in some conditions. For improving the CN and modifying the other properties, and also prevention of phase separation and solving the stability issue of the fuels, it is proposed in this paper


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to use tertiary additives. The content of tertiary additives (CN improvers) is dependent on the fuel properties, oxygenate additives that blended with the diesel fuel, and finally purpose of research. In this study, NM and MXEE were utilized as the CN improver. In this study that used methanol as a fuel additive, CN and viscosity of fuel decrease to 43 and 31.5, respectively. Increasing of the tertiary additives (CN improver) leads to enhancing of CN to 52 and viscosity to 35. Moreover, in this table it is obvious that Nitro methane has a greater impact in improvement of the fuel properties than MXEE. Changing the engine speed and engine load do not have any effect on the fuel properties.

4.4. Responses development and optimization regarding to modeling and adequacy evaluation of model Models could be utilized to estimate all the parameters under study (HC, soot, NOX emissions, BSFC, brake power, CN and viscosity) based on changing of the various variables. This evaluation was known as being useful for the parameters under study were found in accordance with different data and examined scales. The Standard error of NOX and BSFC models for the speed and load of engine variables are shows in Figure 5. This plot indicates in what way the error in the estimated final response varies over the design interval. The plot of standard mean error depends on the standard error of the residuals as well as the location and number of the points of design from the ANOVA results. The Pareto chart of useful and valuable parameters on final models are shown in Figure 6. This figure showed the high effect of engine load as compared to the other variables on all the responses. From Figure 6 it is obvious that the effect of engine speed on the exhaust emissions and engine power is higher than that of nano metallic additives and CN additives, but their effect is smaller than that of the engine load. Moreover, the tertiary additives and nano particle additives have important impact on the formation of soot as compared to the other responses. The cubic charts of the useful parameters with resultant response for models versus experiments results attained at optimum conditions are presented in Figure 7. The boundaries limits (minimum and maximum values) for


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variables and all response have been summarized in Table 6 and Figure 8. Here, a lower value of CV (1.42, 0.78, 4.66, 0.44 and 3.25% for HC, NOx, Soot formations, BSFC and brake power models, respectively) which were attained in this research work have proven a suitable accuracy of the calculation models. The R2 value has nearby amount to one for all responses. In Figure 4, the estimated HC, NOx, Soot emission, BSFC and Power models versus real experiments results are achieved at the optimal terms that seem to give an appropriate conformity between the results from experiments and the predictions processed at the optimum conditions. Meanwhile, almost all the experimental measurements were close enough to the proposed model, such that the plotted line was very close to the model line. This figure showed that the experiment results was nearby to the amounts predicted via the modeling procedure with all the responses being very proper for estimation of the performance of engines and quality of combustion via improved blended fuels.

4.5. Comparison between methanol, ethanol and n-butanol and comparing the related models These models (Table 7) showed the impact of various factors on the diesel emissions. From these models, it is visible that the effect of oxygenate additives on the soot emissions reduction is higher than the other variables. In a model that used methanol (50% oxygen) as an oxygenate additive, the impact of oxygenate additives on reduction of the soot emission was more than the another models. The models showed that the effect of ethanol and normal butanol on BSFC is positive, though this effect is insignificant. However, all of the alcohols (especially methanol) have a noticeable negative effect on the brake power. In these models, it is obvious that oxygenate additive content has a negative effect on the brake power. These models (Table 7) explain that the main effective factors for the fuel properties are the oxygenate and tertiary additives. These models illustrate that the effect of oxygenate additives on is negative on the CN. This is because the CN of ethanol is lesser than that of normal butanol and this factor for methanol is lower than ethanol. In this experimental study, two different nano additives (silica and manganese) are introduced to the diesel-methanol-tertiary additive. From this study, it is evaluated that the effect of both of the nano particles on the engine performance


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(BSFC and engine power) is positive. However, the effect of silica was greater than manganese. Moreover, from Table 7 it is obvious that the effect of nano particle additives on the power is larger than BSFC. Most of the models showed a positive influences of the speed of engine on the power, but the speed has a negative impact on the BSFC and all the exhaust emissions. Load of engine has a positive impact on the exhaust emissions and engine power in most of the results. However, it has a undesirable effect on the BSFC.

5. Conclusion Modeling and optimization of the exhaust gas emission amounts and diesel engine performance are performed, using general experimental design and statistical procedure. The type of CN improver and Nano particle additive, engine load percentage and engine speed are the control issues in this research. Seven models (cubic and quadratic) for CO2, CO, soot, NOx and HC emission amounts, BSFC and power were developed. Our findings show that blending methanol to diesel fuel causes an increase in CO emission higher than other alcohols. With increasing of methanol, the density, CN, kinematics viscosity, and other properties of the fuel have changed. Blending an additive with appropriate properties needs improvement of the fuel properties. Tertiary additives (CN improver additives) could improve the fuel properties, especially when the methanol and ethanol were used as the oxygenated additives. Since n-butanol has closer properties to the diesel fuel (for example its CN is 25). However, the tertiary additives have good potential to reduce the soot emissions. Also, it is obvious from this research that the estimation of the optimum dosage is essential for every nano particle additive. This research showed that the silica has a higher potential for increasing of the engine performance as compared to manganese. Instead, increasing of the speed of engine causes reduction of all air pollutants and has a small positive effect on the engine performance (i.e. BSFC and brake power). However, increasing of the load percentage has a great positive impact on the exhaust emissions. This is because enhancing of the load of engine and decreasing of the speed of engine raises the engine temperature. The new modified fuels in this work will be applied for any diesel engine. Based on the


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Energy & Fuels

results obtained from optimization, the maximum efficiency of the fuel is achieved when nitro methane and silica are used as tertiary and nano additives, respectively.

Nomenclature F-value b0, b1, . . .,bn DOF R CV R2 X1, X2, X3 Y CI UTHC BSFC

Ratio of variances, computed value Regression coefficients Degree of freedom Correlation coefficient Coefficient of variation Coefficient of multiple determinations Coded variables Response Cetane Index unburned total hydrocarbon Brake Specific Fuel Consumption

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Energy & Fuels

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Table 1. Specification of AVL 465 analyzer Table 2. Specification of MRU 1600-L analyzer Table 3. Physico-chemical properties of methanol, n-butanol, ethanol and diesel Table 4. 2-Level factorial design with variables and corresponding actual and coded levels Table 5. The experimental results of modified diesel fuel with engine performance and emissions Table 6. Optimum conditions of diesel fuel blends and their predicted responses Table 7. The impact of various factors on the emissions and engine performance for various diesel blend fuels.


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Energy & Fuels

Fig 1. Photographic view of engine coupled with dynamometer in your test cell Fig 2. The Normal % Probability versus Standardized Effect for (a) HC, (b) NOx, (c) Soot emission and (d) BSFC, (e) Power models Fig 3. The 3D response plots of combined effects of X3 and X4 on the (a) NOx, (b) Soot emission and (c) BSFC, (d) Power Fig 4. Estimated (a) HC, (b) NOx, (c) Soot emission and (d) BSFC, (e) Power models versus actual experimental data obtained at optimum conditions Fig 5. The Standard error of (a) NOx and (b) BSFC model for X3 and X4 variables Fig 6. The pareto chart of effective parameters on (a) HC, (b) NOx, (c) Soot emission and (d) BSFC, (e) Power models Fig 7. The cubic plots of effective variables with corresponding response for (a) NOx, (b) Soot emission and (c) BSFC, (d) Power models versus actual experimental data obtained at optimum conditions Fig 8. Optimum conditions and their results


Energy & Fuels

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Fig 1. Photographic view of engine coupled with dynamometer in your test cell

197x97mm (96 x 96 DPI)


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Energy & Fuels

Fig 2. The Normal % Probability versus Standardized Effect for (a) HC, (b) Nox, (c) Soot emission and (d) BSFC, (e) Power models 254x176mm (96 x 96 DPI)


Energy & Fuels

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Fig 3. The 3D response plots of combined effects of X3 and X4 on the (a) NOx, (b) Soot emission and (c) BSFC, (d) Power 254x174mm (96 x 96 DPI)


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Energy & Fuels

Fig 4. Estimated (a) HC, (b) Nox, (c) Soot emission and (d) BSFC, (e) Power models versus actual experimental data obtained at optimum conditions 254x177mm (96 x 96 DPI)


Energy & Fuels

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Fig 5. The Standard error of (a) NOx and (b) BSFC model for X3 and X4 variables

254x165mm (96 x 96 DPI)


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Energy & Fuels

Fig 6. The pareto chart of effective parameters on (a) HC, (b) Nox, (c) Soot emission and (d) BSFC, (e) Power models

254x176mm (96 x 96 DPI)


Energy & Fuels

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Fig 7. The cubic plots of effective variables with corresponding response for (a) Nox, (b) Soot emission and (c) BSFC, (d) Power models versus actual experimental data obtained at optimum conditions 254x177mm (96 x 96 DPI)


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Energy & Fuels

Fig 8. Optimum conditions and their results

254x164mm (96 x 96 DPI)


Improving the Properties and Engine Performance of DieselâMethanol

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