Fuel 119 (2014) 266–273

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Fuel

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Performance optimization of CI engine fuelled with waste fried oilmethyl ester-diesel blend using response surface methodology

0016-2361/$ - see front matter � 2013 Elsevier Ltd. All rights reserved.http://dx.doi.org/10.1016/j.fuel.2013.11.039

⇑ Corresponding author at: Department of Mechanical Engineering, PadreConceicao College of Engineering, Verna, Goa, India. Tel.: +91 9822347923;fax: +91 832 2791268.

E-mail address: jhirkude@yahoo.com (J. B. Hirkude).

Jagannath B. Hirkude a,b,⇑, Atul S. Padalkar c

a Department of Mechanical Engineering, Sinhgad College of Engineering, Pune, 41 Maharashtra, Indiab Padre Conceicao College of Engineering, Verna, 403722 Goa, Indiac Department of Mechanical Engineering, Flora Institute of Technology, Pune, Maharashtra, India

h i g h l i g h t s

� Experiments were designed using design of experiments based on RSM.� Effect of operating parameters on performance and emissions of CI engine.� Biodiesel from waste fried oil used as fuel for analysis.� Optimization of input parameters using desirability approach of RSM.� Optimal input parameters found were CR = 17.99, IP = 250 bar and IT = 27� BTDC.

a r t i c l e i n f o

Article history:Received 10 May 2013Received in revised form 12 November 2013Accepted 18 November 2013Available online 8 December 2013

Keywords:OptimizationPerformanceWaste fried oil methyl esterResponse surface methodology

a b s t r a c t

The objective of this work is to optimize direct injection, single cylinder diesel engine with respect tobrake power, fuel economy and smoke emissions through experimental investigation and responsesurface methodology. A single cylinder 3.8 kW engine was selected for this experimentation. Threeparameters viz. compression ratio (CR), injection pressure (IP) and injection timing (IT) were variedand the responses like brake thermal efficiency (BTE), Brake Specific Fuel Consumption (BSFC), ExhaustGas Temperature (EGT) and smoke opacity (OP) were investigated. Statistical tool like response surfacemethodology was used to design experiments. Optimization of compression ratio and injection systemparameters was performed using the desirability approach of the RSM for superior performance andlesser smoke emissions. A CR of 17.99, IP of 250 bar, and IT of 27� BTDC were found to be optimal valuesfor the Waste Fried Oil Methyl Esters (WFOME) blended with diesel fuel operation in the test engine of 5HP at 1500 rpm. The results of this study revealed that at optimal input parameters, the values of the BTE,BSFC, EGT and smoke opacity were found to be 29.76%, 0.289 kg/kW h, 298.52 �C and 56.49 HSUrespectively.

� 2013 Elsevier Ltd. All rights reserved.

1. Introduction

Alternate fuels like biodiesel for compression ignition enginesare earning popularity due to the depleting nature of fossil fuelsand adverse environmental effect of exhaust emissions from petro-leum fuelled diesel engines. Currently elevated cost of biodieselproduced from edible and non-edible oil is one of the mainobstructions for its commercialization. Since the cost of vegetableoil is increasing rapidly, it is of concern to biodiesel producers asfeed stock accounts for 70% cost of biodiesel [1]. Waste cooking

oil is one of the major wastes generated in hotels and other publiceateries. Depending on the source and availability, the cost ofwaste cooking oil is about 60% less than fresh vegetable oil [2].Hence biodiesel from waste fried oil can be used as a suitable alter-native for mineral diesel in CI engine after improvement of fuelproperties [3–6]. Many authors have confirmed from their primaryexperimental investigations that fuel with blend of B40 (40% bio-diesel + 60% mineral diesel) gave better performance over otherblend ratios [7–10]. Pandian et al. investigated the effect of injec-tion system parameters such as injection pressure (IP), injectiontiming (IT) and nozzle tip protrusion on performance and emissioncharacteristics of a twin cylinder compression ignition (CI) directinjection (DI) engine fuelled with pongamia biodiesel–diesel blendusing response surface methodology (RSM). The results demon-strated that the brake specific energy consumption (BSEC), Carbon

Table 1Properties of B40 (test fuel).

Properties B40 Diesel (No. 2) Method

Viscosity at 400 �C (cSt) 5.56 4.320 ASTM D445Specific gravity 0.846 0.830 ASTM D941Calorific value (kJ/kg) 41,400 43,000 ASTM D240Flash point �C 120 70 ASTM D93

J. B. Hirkude, A.S. Padalkar / Fuel 119 (2014) 266–273 267

Mono-oxide (CO), Unburned Hydrocarbon (HC) and smoke opacity(OP) were lesser, and brake thermal efficiency (BTE) and NitrogenOxides (NOx) were higher at nozzle tip protrusion of 2.5 mm, IP of225 bar and IT of 30� BTDC [10].

Laguitton et al. studied the effect of reduction in compressionratio (18.4 to 16) on the emissions of a diesel engine [11]. It wasfound that, either reducing the compression ratio (CR) or decreas-ing the IT greatly reduced OP and NOx emissions, although therewas a small CO and HC penalty. Raheman and Ghadge analyzedthe performance of diesel engine using biodiesel by varying CRs(18, 19 and 20). The results depicted that BTE and Exhaust GasTemperature (EGT) increased and Brake Specific Fuel Consumption(BSFC) decreased with the increase in CR [12].

Puhanet al. examined the effect of variation in IP on the perfor-mance and emissions characteristics of a diesel engine by usinghigh linolenic linseed oil methyl ester [13]. It was found that atoptimum IP, the values of BSFC and BTE were found similar tothose when using diesel and also a reduction in OP, CO, and HCemissions with an increase in NOx emissions were observed com-pared to diesel.

Bakar et al. investigated the effect of IP on the performance of aDI diesel engine at 1600 rpm and they found that the best perfor-mance was at 22 MPa, IP [14]. Hyun Kyu Suh conducted experi-mental analysis for a better understanding of the combustionstability and reduction of exhaust emission in low CR engine. Itwas observed that two pilot injectors improve combustion effi-ciency, and result in more stable operation in a low CR engine [15].

Suryawanshi and Desphande studied the effects of decreasedfuel IT (by 4�) on the emissions and performance of a pongamiaoil methyl ester (PME) fueled DI diesel engine [16]. They observedthat the addition of PME to diesel fuel caused a significantreduction in OP, HC and CO emissions but a slight increase inNOx emissions with standard IT. Sayin et al. studied the influenceof CR and injection parameters such IT and IP on the performanceand emissions of a DI diesel engine using biodiesel (5%, 20%, 50%,and 100%) blended-diesel fuel. Tests were carried out using threedifferent CRs (17, 18, and 19/1), ITs (15�, 20�, and 25� Crank Angle(CA) Before Bottom Dead Centre (BTDC)) and IPs (18, 20 and22 MPa) at 20 N m engine load and 2200 rpm. Their observationsrevealed the best results for BSFC and BTE at increased the CR, IP,and original IT. For the all tested fuels, an increase in IP, IT andCR lead to decrease in OP, CO and HC emissions while increase inNOx emissions [17].

The most extensive applications of RSM are in those situationswhere several input variables potentially influence some perfor-mance measure or the quality characteristic of the process. RSMhas been applied for optimization of several chemical andphysical processes [18–20]. Initially, RSM was developed to modelexperimental responses and then migrated into the modeling ofnumerical experiments [21]. Win et al. optimized parameters likeload, speed and static injection timing of a diesel fueled CI engineto reduce noise, fuel consumption and exhaust emissions by usingRSM [22]. Lee and Reitz used RSM to optimize a high speed DIdiesel engine equipped with a common rail injection systemneglecting the interactive effects of the parameters [23]. Satakeet al. performed optimization of the fuel injection control of dieselengines using RSM [24]. Anand and Karthikeyan optimized theengine parameters of a spark ignition engine with gaseous fuelswith the help of Taguchi methodology [25]. The nonlinearoptimization techniques such as RSM, artificial neural network,genetic algorithm fuzzy logic and Taguchi method were used foroptimizing the performance and emission characteristics of dieselengine [25–27].

As seen in literature review CR, IT and IP influences perfor-mance and exhaust emission parameters. Some researchers havestudied effect of these parameters independently. Combined

effects of operating parameters such as CR and injection parame-ters like IT and IP on the smoke emissions and performance of adiesel engine using Waste Fried Oil Methyl Esters (WFOME)–blended diesel fuel have not been studied in detail. Therefore thisstudy highlights the combined effects of CR, IT, IP on the engineperformance and smoke emissions by using RSM. The other objec-tive of the present work is to investigate appropriate input param-eters (CR, IP and IT) for optimal output response parameters (BTE,BSFC, EGT and OP) to design CI engines for specific biodiesel. Opti-mization of input parameters was performed by using desirabilityapproach of RSM.

2. Equipments and material

2.1. Fuel preparations

As confirmed by initial investigation carried out by the differentauthors, blend of B40 was selected because of its better perfor-mance over other blend ratios [7–10]. The biodiesel producedthrough transesterification process from waste fried oil wasblended with diesel, procured from a commercial vendor. A vol-ume ratio of 40:60 is used to get the biodiesel–diesel blend ofB40. To ensure a homogeneous mixture the blending was done justbefore beginning of the experiments. The properties of the fuelblend of B40 and diesel have been determined as per the ASTMstandards in an industrial testing and analytical laboratory, estab-lished at Goa, India. The properties of B40 are tabulated in Table 1.

2.2. Engine set up

The experimental set up consists of a single cylinder dieselengine, air metering unit, fuel measuring equipment, smoke meterand thermocouples with temperature indicator. The schematic dia-gram of test setup is shown in Fig. 1.This unit is manufactured byInd Labs Equipments Bangalore, India. The major specifications ofthe engine used for investigations are presented in Table 2. The en-gine was coupled with a single phase, 230 V AC alternators. Thealternator was used for loading the engine through a resistive loadbank. The load bank consists of eight heaters of 500 W each. Theengine was loaded gradually from 0.5 kW to 3 kW in step of0.5 kW. The engine was first tested with diesel fuel for no loadfor 20 min at rated speed of 1500 rpm until lubricating oil temper-ature rose to around 80 �C. The same conditions were maintainedthroughout the experiment for different test runs.

The specific fuel consumption was computed by measuring thetime taken for a fixed volume of fuel that flows into the engine. Thecurrent and voltage was measured by using ammeter and voltme-ter. The alternator was calibrated for its conversion efficiency. Thebrake power was calculated from the alternator output and its con-version efficiency. The engine speed (rpm) was measured by elec-tronic digital counter. The readings were taken three times for eachrun and the average value was used to calculate performanceparameters and smoke opacity. The performance parameters, BTEand BSFC were calculated from measured data. The Smoke Opacity(OP) was measured by using smoke meter (Make:Netel, India;

1

2

3

7 8

4

1011

9

5

6

Fig. 1. Schematic diagram of experimental setup (1) engine (2) alternator (3)electrical load bank (4) fuel tank (5) burette (6) two way control valve (7) air box (8)orifice plate (9) U tube manometer (10) exhaust gas thermocouple, and (11) smokemeter.

Table 2Engine specifications.

Make Kirloskar (India)

Type 4 Stroke, single cylinderIgnition Compression ignitionRated power 3.78 kW (5 HP)Rated speed 1500 rpmNumber of cylinders 1Bore X stroke 80 � 110 mmCompression ratio 16.5:1Combustion chamber Direct injection with bowl in pistonStandard injection timing 27� BTDCStandard injection pressure 190 BarsStarting Hand crankingLoading By AC single phase alternator, 4 kW (max.)Torque arm distance 0.2 m

268 J. B. Hirkude, A.S. Padalkar / Fuel 119 (2014) 266–273

Model Name: NPM-SM-111B). The smoke opacity was measured inHartridge Smoke Unit (HSU).

All tests were conducted at electrical loading of 3 kW (75% offull load capacity). All together 36 tests were conducted by varyingCR at four levels (16, 17, 18 and 19), IP at three levels (200 bar,225 bar and 250 bar) and IT at three levels (24� BTDC, 27� BTDCand 30� BTDC). All tests were conducted for fuel blend of B40.Uncertainty analysis of measured and calculated parameters ispresented in Table 3.

2.3. Response surface methodology (RSM)

RSM was applied in the present study for modeling and analysisof response parameters in order to obtain the characteristics of the

Table 3Accuracy and uncertainty analysis.

Measured quantity Accuracy Calculatedquantity

Uncertainty

Viscosity ±0.2 cSt Brake power ±2%Time ±0.1 S BTE ±2.15%EGT ±1 �C BSFC ±2.15%Smoke opacity ±1 HSU Specific gravity ±1.5%Calorific value ±0.15 MJ/

kg– –

Speed ±10 rpm – –Current ±0.1 A – –Voltage ±5 V – –Burette fuel measurement ±1 cc – –

engine. The ranges of the input parameters were selected based onthe permissible limits within which the modifications can be madewith the existing engine. Design of Experiments was used to eval-uate the performance of the engine over the entire range of varia-tion of input parameters with minimum number of experiments.The design matrix was selected based on the historical data ofRSM generated from the software ‘‘Design expert’’ trial version8.0.7.1 of Stat ease, US. Experimental design matrix along with re-sponses obtained is presented in Table 4. The responses such asBTE, BSFC were evaluated where as EGT and OP was measured.The experimental readings were fitted to the second order polyno-mial equation using design expert software. A multiple regressionanalysis was carried out to obtain coefficients and the equationsthat can be used to predict the responses. Using the statisticallysignificant model, the correlation between the operating parame-ters and the several responses were obtained. Finally the optimalvalues of engine operating parameters were evaluated by usingthe desirability based approach of RSM.

2.4. Desirability approach for optimization

The optimization analysis can be carried out using DesignExpert software, where each response is transformed to a dimen-sionless desirability value (d) and it ranges between d = 0, whichsuggests that the response is completely unacceptable, and d = 1suggests that the response is more desirable. The goal of each re-sponse can be either maximize, minimize, target, in the rangeand/or equal to depending on the nature of the problem. The desir-ability of the each response can be calculated by the followingequations with respect to the goal of each response.

For a goal of minimum, di = 1 when Yi 6 Lowi; di = 0 whenYi P Highi; and

di ¼ ½ðHighi � YiÞ=ðHighi � LowiÞ�wti when Lowi < Yi < Highi

For a goal of maximum, di = 0 when Yi 6 Lowi; di = 1 whenYi P Highi; and

di ¼ ½ðYi � LowiÞ=ðHighi � LowiÞ�wti when Lowi < Yi < Highi

For a goal as target, di = 0 when Yi < Lowi; Yi > Highi

di ¼ ½ðYi � LowiÞ=ðTi � LowiÞ�wt1i when Lowi < Yi < Ti

di ¼ ½ðYi �HighiÞ=ðTi �HighiÞ�wt2i when Ti < Yi < Highi

For the goal within the range, di = 1 when Lowi < Yi < Highi; anddi = 0; otherwise.

Here ‘‘i’’ indicates the response, ‘‘Y’’ the value of response, ‘‘Low’’represents the lower limit of the response, ‘‘High’’ represents theupper limit of the response, ‘‘T’’ means the target value of the re-sponse, ‘‘wt’’ indicates the weight of the response. The shape ofthe desirability function can be changed for each response by theweight field. Weights are used to give more emphasis to the low-er/upper bounds. Weights can be ranged from 0.1 to 10; a weightgreater than 1 gives more emphasis to the goal, weights less than1 give less emphasis. When the weight value is equal to one, thedesirability function varies in a linear mode. Solving of multiple re-sponse optimizations using the desirability approach involves atechnique of combining multiple responses into a dimensionlessmeasure of performance called the overall desirability function, D(0 6 D 6 1), is calculated by

D ¼ Pni¼1dri

i

� �1=Rri

In the overall desirability objective function (D), each response canbe assigned an importance (r), relative to the other responses.Importance varies from the least important value of 1, indicated

Table 4Design matrix.

Std Run CR IP (bar) IT (BTDC) BTE (%) BSFC (kg/kW h) EGT (oC) OP (HSU)

1 1 16 200 24 24.85 0.341 282 682 2 16 200 27 26.32 0.32 285 653 3 16 200 30 25.64 0.332 288 634 4 16 225 24 26.43 0.329 277 665 5 16 225 27 27.96 0.311 281 636 6 16 225 30 27.4 0.317 284 617 7 16 250 24 26.57 0.326 274 648 8 16 250 27 27.85 0.309 276 619 9 16 250 30 27.28 0.316 279 5910 10 17 200 24 25.7 0.331 293 6511 11 17 200 27 25.57 0.313 297 6412 12 17 200 30 26.23 0.323 301 6013 13 17 225 24 27.24 0.322 288 6414 14 17 225 27 28.91 0.303 291 6115 15 17 225 30 28.27 0.311 296 5916 16 17 250 24 27.35 0.318 285 6217 17 17 250 27 28.9 0.301 288 5918 18 17 250 30 28.2 0.307 291 5719 19 18 200 24 26.08 0.327 301 6320 20 18 200 27 28.29 0.303 306 6121 21 18 200 30 27 0.313 313 5922 22 18 225 24 27.78 0.313 297 6123 23 18 225 27 30.08 0.291 302 5924 24 18 225 30 29.29 0.297 309 5725 25 18 250 24 27.89 0.309 294 5926 26 18 250 27 29.95 0.289 298 5727 27 18 250 30 29.15 0.294 303 5528 28 19 200 24 25.85 0.329 306 6129 29 19 200 27 27.95 0.305 314 5930 30 19 200 30 26.62 0.313 325 5731 31 19 225 24 25.59 0.315 301 5832 32 19 225 27 29.69 0.293 308 5633 33 19 225 30 29.12 0.299 319 5434 34 19 250 24 27.75 0.313 298 5735 35 19 250 27 29.55 0.291 305 5536 36 19 250 30 29.05 0.297 309 53

J. B. Hirkude, A.S. Padalkar / Fuel 119 (2014) 266–273 269

by (+), the most important value of 5, indicated by (+++++). A highvalue of D indicates the more desirable and best functions of thesystem which is considered as the optimal solution. The optimumvalues of factors are determined from value of individual desiredfunctions (d) that maximizes D [10].

3. Results and discussion

3.1. Analysis and evaluation of model

The Analysis of Variance (ANOVA) was used to verify modeladequacy which provides numerical information about P value.Based on the ANOVA, the models were found to be significant asthe values of P were less than 0.05. The regression statisticsgoodness of fit (R2) and the goodness of prediction (Adjusted R2)indicated that the model fits the data very well.

The predicted quadratic models for the responses were devel-oped in terms of non-dimensional coded factors and are givenbelow as Eqs. (1)–(4). These equations are valid for input variableslevels range from 16 to 19 for CR, 200 to 250 bar for IP and 24–30�BTDC for IT. To simplify calculations and analysis, the actualvariable ranges are usually transformed to non-dimensional codedvariables with a range of ±1. In this analysis, the actual range of16 6 CR 6 19 would translate to coded range of �1 6 CRc 6 1.The general equation used to translate from coded to uncoded isgiven below as Eq. (5).

BTE ¼ 29:33þ 0:70CRc þ 0:97IPc þ 0:59ITc þ 0:04� CRc

� IPc þ 0:27� CRc � ITc þ 0:07� IPc � ITc � 0:65

� CR2c � 0:83� IP2

c � 1:4� IT2c ð1Þ

BSFC ¼ 0:3� 8:85� 10�3 � CRc � 7:5� 10�3 � IPc � 6:42

� 10�3 � ITc � 5:5� 10�4 � CRc � IPc � 1:65� 10�3

� CRc � ITc � 3:12� 10�4 � IPc � ITc þ 5:68� 10�3

� CR2c þ 4:92� 10�3 � IP2

c þ 0:014IT2c ð2Þ

EGT ¼ 297:24þ 14:5CRc � 4:62IPc þ 5:04ITc � 0:48� CRc

� IPc þ 2:52� CRc � ITc � 0:88� IPc � ITc � 2:63

� CR2c þ 0:21� IP2

c þ 0:46� IT2c ð3Þ

OP ¼ 59:93� 3:33CRc � 1:96IPc � 2:25ITc � 0:025� CRc

� IPc þ 0:3� CRc � ITc þ IPc � ITc � 0:13� CR2c þ 0:21

� IP2c þ 0:083� IT2

c ð4Þ

xactual ¼ xmin þ ½ðxcoded þ 1Þ=2� ðxmax � xminÞ� ð5Þ

where xactual is the uncoded value, xmin and xmax are the uncodedminimum and maximum values (corresponding to �1 and +1 codedvalues), and xcoded is the coded value to be translated. It may benoted from Eq. (5) that the coded value of 0 corresponds to theactual value xmaxþxmin

2 . Thus coded value of 0 from equations given abovecorresponds to the following actual values: CR = 17.5, IP = 225 barand IT = 27� BTDC. Hence it is expected that corresponding outputgives some numerical values even when coded factors have a valueof 0. Corresponding output numerical values for coded value of 0 fromthe above equations are BTE = 29.33%, BSFC = 0.3 kg/kW h,EGT = 297.24 �C and OP = 59.93 HSU.

270 J. B. Hirkude, A.S. Padalkar / Fuel 119 (2014) 266–273

3.2. Interactive effect of CR and IP

BTE at different CRs and IPs is depicted in a three dimensionplot (Fig. 2a). As seen in figure, for all IPs, the BTE increases withincrease in CR (from 16 to 18) and decreases slightly with furtherincrease in CR (from 18 to 19). At IT of 27� BTDC, increase CR from16 to 17 and from 17 to 18 increased BTE by 2.61%, and 3.54%respectively. Further, increase in CR from 18 to 19 lead to decreasein BTE by 0.384%. The minimum auto-ignition temperature of afuel decreases due increased density of the compressed air. This re-sults in a closer contact between the molecules of fuel and oxygenreducing the time of reaction. The increase in the compressiontemperature as well as the decrease in minimum auto-ignitiontemperature decreases the delay period [28]. Initial increase inBTE with increase in CR could be attributed to enhancement ofdensity of intake air and reduction in ignition delay associated withit. Minor reduction in BTE beyond compression ratio of 18 could beattributed to insufficient combustion space because of furtherreduction in clearance volume. Small (insufficient) combustionchamber volume causes the injected fuel particles to hit to com-bustion chamber wall and may lead to incomplete combustion[10]. The change in BSFC at different IPs and CRs is presented inFig. 2b. As illustrated in figure the BSFC was found decreasing withincrease in CR from 16 to 18. The possible reason for this trendcould be that, with an increase in CR, the maximum cylinder pres-sure increases due to the fuel injected in hotter combustion cham-ber and this leads to higher effective power. Therefore, fuelconsumption per output power will decrease [29]. From CR of 18onwards minor increase in BSFC was observed. The possible reasonfor this trend could be insufficient combustion space (because of

Fig. 2. Interactive eff

very less clearance volume at higher CR), which leads to slightreduction in effective power. The variation of EGT for differentCRs and IPs is shown in Fig. 2c. At higher CRs increase in EGTwas observed and the possible reason for this could be higher oper-ating temperature at elevated CRs [2]. The interactive effect of CRand IP on OP is depicted in Fig. 2d. Smoke emissions at higherCRs were observed lesser than at lower CRs. This could be becauseof better combustion efficiency due to higher temperature andpressure at higher CRs [30].

3.3. Interactive effect of IP and IT

As seen in Fig. 3a, the BTE increases with increase in injectionpressure. Higher fuel injection pressures increase the degree ofatomization. The fineness of atomization reduces ignition delay,due to higher surface volume ratio [30]. At 27� BTDC, with increasein IP from 200 to 225 bar, average BTE increased by 3.41%. Further,increase in IP from 225 to 250 bar, leads to increase in BTE just by0.88%. This could be because of improved spray characteristics,better atomization and good mixing with air at higher IPs. This willimprove efficiency because of enhancement in combustion pro-cess. A very high IP leads to finer diameter of fuel droplet; this af-fects the spray pattern and penetration. Too fine droplet size willhave low depth of penetration due to less momentum of the drop-let and velocity relative to air from where it has to find oxygenafter vaporization [30]. Therefore only minor increase in BTE wasobserved from 225 to 250 bar IP. The other reason for negligibleimprovement in efficiency could be that beyond 225 bar pressure,faster velocity of fuel jets caused most fuel particles to hit the wallof combustion chamber where fuel particles get cooled which may

ect of IP and CR.

Fig. 3. Interactive effect of IT and IP.

J. B. Hirkude, A.S. Padalkar / Fuel 119 (2014) 266–273 271

result in incomplete combustion [9]. Fig. 3b demonstrates thechange in BSFC at different IPs and ITs. The reduced BSFC valueswere obtained with increase in IP (from 200 to 225 bar). This couldbe because of finer atomization and improved mixing at higherinjection pressure [31]. Marginal decrease in BSFC was observedwith increase in IP from 225 to 250 bar because of minor increasein BTE. Brake specific energy consumption at CR of 17 (for 270

BTDC and 200 bar) was 12,960 kJ/kW h.Variation in EGT with different IPs and ITs is shown in Fig. 3c.

There was increase in EGT with increase in IP. This may be attrib-uted to the increased cylinder pressure due to improved combus-tion of fuel as a result of improved atomization and bettermixing [31].

Fig. 3d explains variation in OP at different IPs and ITs. Decreasein OP with increase in IP was observed. This could be, as a result offiner particle diameter at higher IP. Therefore, fuel-mixture wouldbecome better through the combustion period which leads to lesssmoke emission [30].

3.4. Interactive effect of IT and CR

The change in BTE at different ITs and CRs is observed in Fig. 4a.BTE decreases with advancement of IT from 27� BTDC to 30 BTDC,even retardation of IT from 27� BTDC to 24� BTDC leads to decreasein BTE. This can be attributed to increase ignition delay associatedwith increase in injection time angle. Whereas retardation of injec-tion timing by 3� (24� BTDC) decreases delay period which couldlessen the brake power due to burning of larger quantity of fuelduring expansion [2].

The variation of BSFC for different CRs and ITs is shown inFig. 4b. At CR of 18 with increase in IT from 24 to 27� BTDC leads

to decrease in average BSFC by 6.95%. While further increase inIT from 27 to 30� BTDC resulted in increase in BSFC by 2.37%. Withadvancement of IT from 27� BTDC to 30� BTDC the ignition delaywould be longer and flame speed may be lower. These cause reduc-tion in brake power. But retardation of IT from 27� BTDC to24� BTDC leads to late combustion and therefore pressure rises ata later stage of the expansion stroke. These cause reduction ineffective pressure which could be responsible for reduction inbrake power and reduction in BSFC [2]. BSEC at 27� BTDC (for CRof 18 and IP of 250 bar) observed was 12,050 kJ/kW h.

Fig. 4c illustrates effects of IT and CR on EGT. As seen in Fig. 4c,decrease in EGT was observed with increase in IT. Advancement ofinjection timings may lead to an early start of combustion relativeto TDC which increases chances of complete combustion andreduces the EGT [2]. Fig. 4d explains the variation of OP for differ-ent ITs and CRs. Because of advancement of injection timings from24� BTDC to 30� BTDC, OP was reduced. Finer break up fuel drop-lets obtained with increased IP provide more surface area and bet-ter mixing with air and this effect improves combustion [18]. Asthe pressure and temperature at the beginning of the injectionare lower for higher ignition advance, the delay period increaseswith increase in injection advance [28]. This could be attributedto the following fact: advancement of injection timing means ex-tended ignition and decrease in charge temperature and pressure[2].

3.5. Optimization

The comprehensive discussions on the effect of CR, IP and IT onperformance and smoke emission characteristics have shown thatthe lowest IP of 200 bar, retarded IT of 24� BTDC and CR of 16

Fig. 4. Interactive effect of IT and CR.

Table 5Optimization of individual parameters.

Parameter Optimized value Criteria CR IP (bar) IT (�BTDC) Desirability

BTE (%) 29.946 Maximize 18.43 240.41 27.97 0.974BSFC (kg/kW h) 0.288 Minimize 18.67 237.79 27.62 1.000EGT (�C) 274.98 Minimize 16.00 250.00 24.00 0.981OP (HSU) 52.902 Minimize 18.99 249.99 29.93 1.000

Table 6Optimization criteria and desirability of responses for performance parameters.

Parameter Limits Weight Importance Criterion Desirability

Lower Upper Lower Upper

CR 16 19 1 1 3 In range 1IP (bar) 225 250 1 1 3 In range 1IT (BTDC) 27 30 1 1 3 In range 1BTE (%) 20 30.86 0.1 1 5 Maximize 0.93BSFC (kg/kW h) 0.289 0.341 1 0.1 5 Minimize 0.956EGT (�C) 274 325 1 0.1 5 Minimize 0.519OP (HSU) 53 68 1 0.1 5 Minimize 0.769Combined – – – – – – 0.778

272 J. B. Hirkude, A.S. Padalkar / Fuel 119 (2014) 266–273

resulted in low values of BTE and EGT with high values of BSFCand OP. An IP of 250 bar with an IT of 27� BTDC and CR of 18 causedhigher BTE and EGT with lower values of BSFC and OP. Optimisa-tion of individual performance and emission parameters forindependent input variables like CR, IP and IT are tabulated inTable 5.

As there was a trade-off between BTE, BSFC, OP and EGT, it wasnecessary to optimize the CR, IP and IT with the goal of minimizingsmoke emission and maximizing the BTE without compromisingBSFC and EGT. The criteria for the optimization such as the goalset for each response, lower and upper limits used, weights usedand importance of the factors is shown in Table 6. In desirability

J. B. Hirkude, A.S. Padalkar / Fuel 119 (2014) 266–273 273

based approach the solution with high desirability was favoured.Maximum desirability of 0.778 was obtained at CR of 17.99, IT of27.8� BTDC and IP of 250 bar, which could be considered as theoptimum parameters. BSEC at optimal input parameters was ana-lysed as 11,970 kJ/kW h.

4. Conclusions

In this study biodiesel from waste fried oil blended with min-eral diesel was used to investigate effects of significant operatingparameters like CR, IT and IP on performance and emission of com-pression ignition engine. Based on the results of this study the fol-lowing conclusion can be drawn.

1. RSM based design of experiments was used to design and carryout statistical analysis to determine parameters which have themost significant influence on the performance and smoke emis-sion characteristics. Desirability approach of the RSM was usedto find out optimum parameters for optimization of perfor-mance and smoke emission characteristics.

2. Increase in compression ratio increases brake thermal efficiencyfor all injection pressures and injection timings of the engine.Beyond CR of 18, decrease in trend in BTE was observed. Brakethermal efficiency was found to increase with increase in injec-tion pressure. Maximum brake thermal efficiency was observedwith original engine injection timing.

3. Initial decrease in BSFC was observed with increase in CR (from16 to 18) and then starts increasing (from 18 to 19). MinimumBSFC was observed at original injection timing of 27� BTDC.With increase in IP there was decrease in BSFC. Intensity ofdecrease in BSFC from 225 to 250 bar injection pressure wasmarginal.

4. EGT was found to increase with increase in CR and IP, while EGTwas observed decreasing with increase in IT. OP was reduced athigher CR. It was seen that advancement in injection timinglead to reduced smoke emissions. Decrease in OP with increasein IP was also observed.

5. At optimum input parameters viz. CR of 17.99, IP of 250 barwith IT of 27� BTDC, the values of the BTE, BSFC, EGT and smokeopacity were found to be 29.76%, 0.289 kg/kW h, 298.52 �C and56.49 HSU respectively.

6. By properly controlling CR, IP and IT, performance can beimproved and smoke emissions can be controlled by using ablend of alternate fuel like biodiesel from waste fried oil.

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