Combustion_optimization_of_62.5_kva_gens.pdf

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2018-01-0239 Published 03 Apr 2018

Combustion Optimization of 62.5 kVA Genset Engine to Meet CPCB II Norms Using Taguchi Method Victor Debnath PGET, Escorts Yasheshwar Prajapati Asst. Manager, Escorts Kanwal Bali Senior Manager, Escorts Brijesh P Patel Deputy Manager, ARAI Citation: Debnath, V., Prajapati, Y., Bali, K., and Patel, B.P., “Combustion Optimization of 62.5 kVA Genset Engine to Meet CPCB II Norms Using Taguchi Method,” SAE Technical Paper 2018-01-0239, 2018, doi:10.4271/2018-01-0239.

Abstract

number of experimental runs and still get the essence of large number of test runs. Hot (350 °C to 450 °C) and cold (200 °C to 250 °C) exhaust gas recirculation (EGR), EGR tube diameter, injection timing, nozzle tip protrusion and dimensions of high pressure fuel pipe (HPFP) are considered as important parameters for DOE in this work. Results of the study showed that a combination of cold EGR having 10 mm EGR tube diameter, 9 CAD bTDC injection timing, nozzle tip protrusion with 3 mm thick copper washer and 6 mm × 1.5 mm × 450 mm HPFP dimensions is an optimum operating condition for the engine. It has also been observed that EGR and injection timing played a major role to control emissions and brake specific fuel consumption as compared to the other two parameters. From the in-cylinder pressure analysis, it is noticed that EGR concentration altered the peak cylinder pressure whereas retard injection timing shifted the pressure curve towards expansion stroke and slow down the reactions.

D

iesel engines are one of the primary mode of power generation in India due to its higher thermal efficiency and greater torque. In one hand, the demand for higher brake horse power genset is growing in India and the other hand, the stringent engine emission norms are going to be imposed to control the air pollution. In present scenario, the major challenges countered by the automobile industries are to design the engines which meet the norms along with high load capacity with least modifications in existing design. Optimization of various parameters is considered as a viable solution. Full factorial experimental study (large numbers of experiments) is required to be carried out to evaluate the effects of all the parameters on performance and emissions of the engine which is time consuming as well as expensive. As an alternative, a statistical tool called design of experiments (DOE) of the Taguchi method can be used to reduce the

Introduction

like number of holes, angle of injection (vertical), injector protrusion and injection pressure [3]. Moreover, exhaust gas recirculation (EGR) is also considered as one of the crucial parameter since it controls the formation of NOx emission [4]. A longer nozzle protrusion could reduce combustion noise moderately however, it caused severe smoke and

D

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TABLE 1  The CPCB II emission norms in India [2]

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ue to higher thermal efficiency, better brake specific fuel consumption (BSFC) and high torque, diesel engines are dominating in the various applications such as locomotive, agri machinery, construction machinery, genset etc. Diesel engines are also favorable for producing much lower greenhouse gases (GHG) compared to gasoline engines [1]. On the other hand, oxides of nitrogen (NOx) and particulate matter (PM) coming out from diesel engines are a major concern because of their negative impact on environment as well as on human health. Hence, regulatory bodies are continuously imposing stringent emission norms. The current central pollution control board (CPCB-II) emission norms in India for genset engines is given in Table 1 [2]. In direct injection diesel engines, the most important parameters for combustion optimization are piston bowl design, injection timing along with injector’s configuration

Power Range

HC + NOx CO PM Smoke* Date of Implementation (g/kWh) m−1

Up to 19 kW

1.7.2013

7.5

3.5

0.3 0.7

> 19 kW up to 1.7.2013 75 kW

4.7

3.5

0.3 0.7

> 75 kW up to 1.7.2013 800 kW

4.0

3.5

0.2 0.7

* Smoke limit is applicable to all 5 modes.

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Experimental Methodology

carbon monoxide (CO) emissions and moderately increased BSFC. Hence, a shorter protrusion can be preferred [5]. The effect of dimensions of high pressure fuel pipe (HPFP) on emissions cannot be neglected since the longer fuel pipe length causes proportional retardation of the fuel injection time. The higher nozzle opening pressure resulted in increasing the maximum fuel pressure and shorter combustion duration [6]. Various studies have been conducted for optimizing parameters using Taguchi design method [5, 6, 7, 8, 9]. Sivaramakrishnan et al. [7] optimized the brake power of diesel engine by using Taguchi method. Their results showed that brake thermal efficiency (BTE), BSFC and emissions of diesel engine depend upon biodiesel blend, compression ratio, nozzle opening pressure and fuel injection timing. Win et al. [5] had optimized static injection timing, nozzle tip protrusion, number of injector holes, valve opening pressure, nozzle hole diameter and plunger diameter with respect to combustion noise, engine speed, torque, smoke level, fuel economy and emissions of a diesel engine. Brijesh et al. [8, 9] optimized the injection timing, compression ratio and amount of ultracooled EGR for a variable compression ratio engine using Taguchi method. Their results showed that a combination of retarded injection and moderate EGR provided better efficiency in case of low temperature combustion. These studies also showed that the Taguchi methods provide an effective solution when it is needed to quantify the performance and emission with respect to designing parameters. Taguchi has introduced the loss function concept which combines cost, target and other variations. The signal to noise ratio (S/N) is a figure of merit and relates inversely to the loss function. It can be defined as the ratio of amount of energy for intended function to the amount of energy wasted. There are three types of S/N ratios; the lower-the better, the higherthe better, and the more nominal the better. These three S/N ratios are expressed in Table 2 where n and Y are the number of repeated experiments and the measured value of the response variable respectively [10, 11, 12]. “The lower- the better” is being taken as a quality characteristic, since the objective function of the work is to minimize BSFC, NOx, CO, HC and PM. The objective of this work is to design genset engine which comply CPCB II emission norms by doing least modifications in the existing engine. Also, identify an optimum engine operating parameters which offers maximum potential for reducing emissions and improving fuel economy.

In this work, the experiment is carried out with 62.5 kVA diesel engine which is generally used for genset application. The specification of the test engine is provided in Table 3. The engine is coupled with eddy current dynamometer for loading and measuring engine torque and brake power. A pictorial view of the test setup is provided in Figure 1. The apparatus such as inlet air temperature and pressure sensors, exhaust gas temperature sensor, oil pressure sensor, air conditioning specialist (ACS) unit, fuel consumption meter etc. are used. For measurement of NO x, HC and CO emissions, high complexity laboratory director (HCLD), high flux isotope reactor (HFIR) and non-dispersive infrared (NDIR) are used respectively. The set up for the test also consists of four units crank detection module (CDM) that measures the crank angle, pickup that measures the fuel pressure at pump end or cylinder as required, transducer that measure in-cylinder pressure and a special injector nozzle with displacement sensor for needle lift measurement. These units send signal to the indimeter which is connected to a computer for recording data and display the readings. TABLE 3  Test engine specifications

Engine Make

ESCORTS

Engine Model

G62.5kVA

Type of Engine

4-Stroke, Turbocharged Diesel Engine

No of Cylinders

4

Bore (mm)

98

Stroke (mm)

122

Total Swept Volume (Litre)

3.68

Compression Ratio

17.5:1

Type of Combustion Chamber

Re-entrant

Combustion Type

Direct Injection (DI)

Rated Speed (RPM)

1500

Fuel Injection Pump Make-Type-Model

Bosch-Inline-E040326400

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2

 FIGURE 1   Engine test setup

TABLE 2  S/N ratios formulations

The higher – The better

æ S = -10log ç N ç è

åY

The nominal – The best

S æ -2 ö = -10log ç Y 2 ÷ N ès ø

n

2

ö ÷÷ ø

1 ö 2 ÷ ÷ n ø

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åY

© SAE International

æ S = -10log ç ç N è

The lower – The better

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COMBUSTION OPTIMIZATION OF 62.5 kVA GENSET ENGINE TO MEET CPCB II NORMS USING TAGUCHI METHOD

Test matrix is generated as per the Taguchi orthogonal array technique using the Minitab software. Experiments were designed to study the effects of five parameters: hot or cold EGR, EGR tube diameter (see Figure 2), injection timing, nozzle tip protrusion and high pressure fuel pipe (see Figure 3) dimension on fuel consumption and emissions. Based on literature study and engine existing configuration, five design factors and their respective levels, as given in Table 4, are chosen. In this experiment, L18 orthogonal array (OA) has been selected based on the number of parameters and their levels. The test matrix, as generated using Taguchi OA L18 design {partial factorial (18 runs only) for defined factors and their levels for which full factorial runs (maximum possible runs) would be 21 × 34 = 162, where 2, 3 defines number of levels and superscript 1, 4 defines the number of factors}, is depicted in Table 5. The experimental goal is to determine the settings of the critical factors that will create a desired response, such as a maximum or a minimum value, a target value or a target range. Accomplishing this goal is often a two-step process.

TABLE 4  Influence parameters and their levels chosen for

combustion optimization

Level 3

EGR Type

2

Cold

Hot

-

EGR Tube Diameter (mm)

3

5

7

10

Injection Timing (CAD bTDC)

3

9

10

11

Nozzle 3 Protrusion (mm)

2

3

4

3 High Pressure Fuel Pipe (HPFP) Dimension (OD×ID×length) (mm×mm×mm)

6×1.8×450 6×1.5×450 6×1.8×580

Hot or Run Cold No. EGR

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© SAE International

Level 2

TABLE 5  Taguchi orthogonal array L18

 FIGURE 2   EGR tube with intercooler 1) EGR tube 2) cooler assembly 3) EGR tube gasket 4) bolt (white passivated) 5) EGR tube guard

 FIGURE 3   High pressure fuel pipe (HPFP)

No. of Levels Employed Level 1

Influence Parameter

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EGR Tube Diameter (mm)

Injection Nozzle Timing Protrusion (CAD (mm) bTDC)

High Pressure Fuel Pipe Dimension (O.D×I.D×L) (mm×mm×mm) 6 × 1.8 × 450

1

Cold 5

9

2

2

Cold 5

10

3

6 × 1.5 × 450

3

Cold 5

11

4

6 × 1.8 × 580

4

Cold 7

9

2

6 × 1.5 × 450

5

Cold 7

10

3

6 × 1.8 × 580

6

Cold 7

11

4

6 × 1.8 × 450

7

Cold 10

9

3

6 × 1.8 × 450

8

Cold 10

10

4

6 × 1.5 × 450

9

Cold 10

11

2

6 × 1.8 × 580

10

Hot

5

9

4

6 × 1.8 × 580

11

Hot

5

10

2

6 × 1.8 × 450

12

Hot

5

11

3

6 × 1.5 × 450

13

Hot

7

9

3

6 × 1.8 × 580

14

Hot

7

10

4

6 × 1.8 × 450

15

Hot

7

11

2

6 × 1.5 × 450

16

Hot

10

9

4

6 × 1.5 × 450

17

Hot

10

10

2

6 × 1.8 × 580

18

Hot

10

11

3

6 × 1.8 × 450

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Minitab performs a test on the initial modeling design to see if there is curvature in the continuous factors. If curvature is detected, the second step is to add more runs to the design so as to model the curvature and use that model to determine the best settings for the critical factors. The chosen 18 runs will give the optimized parameters for low NOx, HC, CO, PM and BSFC (refer Figure 7). On the basis of optimized output from 18 runs, additional 5 runs have been conducted (refer Table 7) and then the final optimum combination of para­ meters was decided for the engine. Hence, total 18 + 5 = 23 runs were experimentally conducted to get the optimized para­meters for the engine. All 23 runs were carried out for 5 loads i.e. 10%, 25%, 50%, 75% and 100% load as defined in ISO 8178 [13]. © 2018 SAE International. All Rights Reserved.

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COMBUSTION OPTIMIZATION OF 62.5 kVA GENSET ENGINE TO MEET CPCB II NORMS USING TAGUCHI METHOD

Performance and emission data discussed in the work are weightage averaged value of all modes. Weighting factor allocated for 10%, 25%, 50%, 75% and 100% load is 0.1, 0.3, 0.3, 0.25 and 0.05 respectively, as defined in ISO 8178 [13].

because the temperature of the hot EGR impacts the intake mixture temperature and therefore NOx emission increases, as can be seen in Figure 4a, and at the same time PM is decreased as compared to cold EGR. Cooled EGR would increase temperature differential term in the heat absorption Eq. 1, increasing the heat absorbing capacity and further reduce NOx.

Results and Discussion



The experimental data of each levels and parameters were analyzed through analysis of variance (ANOVA) in Minitab to get the optimized value for low emissions and BSFC. Figures 4 to 6 demonstrate the influence of each parameter on emissions and BSFC using signal to noise (SN) ratio analysis. The SN ratios for different emission responses were calculated at each factor level and the average effects were determined by taking the total of each factor level and dividing by the number of data points in that total. The greater difference between the levels, the parametric influence will be much. The parameter level having the highest SN ratio corresponds to the parameters setting indicates lowest emissions and BSFC. Figure 4 shows the variation of SN ratio as a function of cold and hot EGR. As shown in Figure 4a to 4c, SN ratio for CO, HC, PM and BSFC is increased with hot EGR. However, reduction in SN ratio for NOx is observed with hot EGR. It is

DQ = m × C p × DT (1)

where, ∆Q = Increase in heat absorption of the nonreacting gases (Joule), m = Mass in the cylinder (g), Cp = Specific heat capacity at constant pressure (J/g  K), ∆T  = Temperature difference between in-cylinder gases and EGR (K). Moreover, cold EGR impacts the in-cylinder temperature beside charge dilution, which decreases the rate of pressure rise at all loads and at all EGR ratios due to these higher BSFC can be seen in Figure 4c as compared to hot EGR. It indicates the poor combustion with cold EGR as compared to hot EGR which causes more emission of unburned HC and CO with cold EGR (see Figure 4b). The factor effect analysis shows that most of the response variables are found optimal at hot EGR where as cold EGR is beneficial for NOx reduction which is important parameter to meet CPCB II emission norms [2]. Figure 5a to 5c explain the variation of SN ratio as a function of EGR tube diameter which indirectly controls the percentage of EGR. Increase in recirculation of burnt gas  FIGURE 5   Effect of EGR tube diameter on a) PM, NOx, b) CO, HC and c) BSFC

 FIGURE 4   Effect of cold and hot exhaust gas recirculation

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© SAE International

on a) PM, NOx, b) CO, HC and c) BSFC

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COMBUSTION OPTIMIZATION OF 62.5 kVA GENSET ENGINE TO MEET CPCB II NORMS USING TAGUCHI METHOD

5

reduces the proportion oxygen present in the cylinder which is available for combustion. These may result in a correspondingly lower heat release and lower peak cylinder temperature [14] and hence reduce the formation of NOx and increase PM formation, as can be seen in Figure 5a. Figure 5b shows that HC and CO emission increase with increasing EGR percentage. This can be attributed to the reduction of available oxygen to combine with carbon which results to higher CO emission. And as the fuel-air ratios get too rich for complete combustion due to lack of oxygen, the unburned HC increases [15, 16]. The role of EGR is to act as an inert diluents and heat sink that reduces the oxygen concentration during combustion and lowers the combustion temperatures. BSFC increases with the increase of EGR which can be seen in Figure 5c. It may happen because more fuel is required to inject to overcome dilution effects of incoming charge, increase specific heat of exhaust gases, decreasing rate of heat release and rate of reactions of different species [16]. Figure 6a to 6c show the variation of SN ratio as a function of injection timing. The advance injection timing causes higher cylinder temperature and it increases the oxidation process between carbon and oxygen molecules. This causes reduction in CO emissions as shown in Figure 6b. Moreover, early injection results to higher ignition delays and sufficient time for premixing of fuel and air. As a result of increased

premixed phase of combustion and reduced mixing controlled combustion, higher NOx formation and lower soot formation with advance injection timing can be observed in Figure 6a. Ambient air temperature and pressure during early injection timing become lower as compared to retard injection timing, so ignition delay increases. On other hand, if injection starts later (closer to TDC), the temperature and pressure is initially slightly higher. However, both physical and chemical reactions must take place before a significant fraction of the chemical energy in the fuel is released. These reactions need a finite time to occur. Nevertheless, as ignition delay proceeds, the in-cylinder temperature and pressure decreases and reduce the favorable conditions for ignition. The most favorable timing for ignition lies in between these two conditions which is 10 CAD bTDC in this case for lesser HC emission and minimum fuel consumption as shown in Figure 6b and 6c. Figure 7 shows the variation of SN ratio as a function of nozzle tip protrusion. In general, when the spray targeting at the lowest point of the interacting feature (lip of the piston bowl) then the mixing process is sufficiently poor and the impact of fuel on the lip aids the fuel mixing process hence fuel consumption deteriorates with an increase in protrusion (refer Figure 7c). It is important to spray fuel onto the secondary pip in the right location [17]. The turnover in the

 FIGURE 6   Effect of injection timing on a) PM, NOx,

 FIGURE 7   Effect of NTP washer width on a) PM, NOx,

b) CO, HC and c) BSFC

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© SAE International

b) CO, HC and c) BSFC

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COMBUSTION OPTIMIZATION OF 62.5 kVA GENSET ENGINE TO MEET CPCB II NORMS USING TAGUCHI METHOD

response observed with decreasing protrusion could be due to the negative effect of spraying fuel into the squish regions, where temperatures and turbulence may be too low for proper oxidation and combustion. And hence, with 3  mm thick washer, combustion temperatures are found low enough to enable the formation of PM, reduction in NOx emission and BSFC (see Figure 7a and 7c). Targeting the spray lower in the bowl reduces HC and CO emissions because of over lean mixture formed from injected directly into the squish volume which is an important source of these emissions hence 4 mm has higher SN ratio (see Figure 7b). Similar results were noticed by Paul et al. [17] during their study. The variation of SN ratio as a function of high pressure fuel pipe (HPFP) can be seen in Figure 8a to 8c. Increase in inner diameter of fuel pipe causes advancing of fuel injection and increasing injection duration, resulting in lower BSFC and PM with increased NO x emissions [18]. As BSFC decreases with increasing HPFP inner diameter, it indicates more efficient and complete combustion took place; hence HC and CO emissions, as shown in Figure 8b, are also found lower. As the HPFP length increases, fuel injection pressure arrives at the nozzle later which causes proportional retardation of the fuel injection time. Due to which comparatively more amount of fuel is required to inject to gain the same  FIGURE 8   Effect of high pressure injection pipe on a) PM,

NOx, b) CO, HC and c) BSFC

amount of power and hence the BSFC is observed higher (see Figure 8c). Due to the later start of injection, ignition delay may decrease resulting lower premixed peak and lower in-cylinder temperature might be noticed which causes decrease in NOx emission and increase in PM emission. The effect of HPFP length on HC and CO emissions is comparatively observed insignificant (see Figure 8b). The ANOVA technique is carried out to identify the most significant factors and their contribution over the response parameters (see Table 6). F-test names after R.A Fischer checks the significance of variance on the output characteristics. As the F-value increases the effect of that particular factor on output also increases, which has been stack out by name contribution percentage in Table 6. Once the random order is generated, the N objects are to be broken into g (number of levels) subsets with sizes n1, n2, …, ng with n1 + n2+ · · · + ng = N. The degrees of freedom (DF) are g − 1 for treatments. The formulae for sums of squares are given in Eq. 2, and mean squares are always sums of squares divided by their degrees of freedom as mentioned in Eq. 3. The F-value is the ratio of two mean squares, the numerator mean square for a source of variation that needs to be assessed, as mentioned in Eq. 4. In Table 6, F-value is used to make a test of the null hypothesis that all the treatment means are the same versus the alternative that some of the treatment means differ. When the null hypothesis is true, the F-value is about 1, give or take some random variation; when the alternative is true, the F-value tends to be bigger than 1. To complete the test, the F- value needs to be found. The F-value quantifies the role of each parameter in the experiment [11]. n

SST =



å( y - y ) (2) 2

i

i =1

MST =



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F=

SST (3) DF ( SST )

variation between the groups (4) variation within the groups

where, SST is the sum of squares, MST is the mean squares, yi  is the ith observation, n is the number of observations, y is the mean of the n observations and DF is the degree of freedom. If the F-value of a parameter for a definite factor is larger it means the effect of that particular parameter is more as compared to other parameters to decide the fluctuation of that factor, because the variation between the groups is more than that of variation within the group and vice versa when the F-value of a parameter for a define factor is smaller. Table 6 depicts hot and cold EGR play a major role to decide NOx and PM emissions along with BSFC as the F-value is more in those cases. On other hand, injection timing is seen as an important parameter to control HC and CO emissions followed by EGR, considering the fact of increased F-value. On the basis of ANOVA test, 5 additional runs, as mentioned in Table 7, are formulated with optimized parameter for each output factors. Based on requirement, an optimum combination can be selected. © 2018 SAE International. All Rights Reserved.

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COMBUSTION OPTIMIZATION OF 62.5 kVA GENSET ENGINE TO MEET CPCB II NORMS USING TAGUCHI METHOD

7

TABLE 6  ANOVA response table

Source

DF

Seq SS

BSFC

Adj SS

Adj MS

F-Value

Contribution Percentage

Adj SS

EGR

1

7.3038

7.304

7.3038

35.17

68.73

EGR Tube Diameter

2

1.6096

1.610

0.8048

1.34

15.15

Injection Timing

2

1.1280

1.128

0.5640

0.89

10.62

Nozzle Protrusion

2

0.3334

0.3334

0.1667

0.24

3.14

HPP Dimension

2

0.2515

0.2515

0.1257

0.18

2.37

Error

0.0000

NOx EGR

1

13.9868

2.6198

2.6198

130.66

97.76

EGR Tube Diameter

2

0.2855

0.2855

0.1428

0.81

2.00

Injection Timing

2

0.0223

0.0223

0.0112

0.06

0.16

Nozzle Protrusion

2

0.0069

0.0069

0.0034

0.02

0.05

HPP Dimension

2

0.0061

0.0061

0.0030

0.02

0.04

Error

0.0000

CO EGR

1

0.1625

0.1624

0.1625

5.79

26.59

EGR Tube Diameter

2

0.0518

0.0518

0.0259

0.69

8.48

Injection Timing

2

0.3891

0.3891

0.1946

13.15

63.68

Nozzle Protrusion

2

0.0058

0.0059

0.0029

0.07

0.96

HPP Dimension

2

0.0018

0.0018

0.0009

0.02

0.30

0.00003

0.000032

3.41

17.49

Error

0.0000

HC EGR

1

0.00003

EGR Tube Diameter

2

0.00002

0.00002

0.000011

1.01

12.02

Injection Timing

2

0.00008

0.00008

0.000038

5.45

42.08

Nozzle Protrusion

2

0.00001

0.00001

0.000001

0.12

1.64

HPP Dimension

2

0.00001

0.00001

0.000003

0.27

3.28

Error

0.00004

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PM EGR

1

0.0101

0.01008

0.01008

53.91

77.11

EGR Tube Diameter

2

0.0015

0.00150

0.00075

0.97

11.49

Injection Timing

2

0.0010

0.00104

0.00052

0.65

7.93

Nozzle Protrusion

2

0.0001

0.00004

0.00002

0.02

0.31

HPP Dimension

2

0.0001

0.00008

0.00004

0.05

0.64

Error

0.0003

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TABLE 7  Optimum setting table

EGR Tube Run EGR Diameter No. Factors Type (mm)

Injection Timing (CAD bTDC)

NTP (OD×ID×L) (mm) (mm×mm×mm)

19

Low BSFC

Hot

10

3

6 × 1.8 × 450

20

Low NOx

Cold 10

9

3

6 × 1.5 × 450

21

Low CO

Hot

5

11

4

6 × 1.8 × 580

22

Low HC

Hot

5

10

4

6 × 1.8 × 580

23

Low PM Hot

5

11

2

6 × 1.5 × 450

5

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HPP

Test data has been plotted in Figure 9 which shows BSFC lies in margin from 155.2 g/kWh to 153.3 g/kWh, NOx lies in between 2.9 g/kWh to 4.1 g/kWh and PM is falling between 0.17 g/kWh to 0.257 g/kWh. It can be noticed that HC and CO emissions for all five runs, as proposed in Table 7, are falling within the margin as depicted by CPCB II norms (refer Table 1). Considering NOx and PM emissions as an important outcome, optimization point for low NOx is far better than the low PM. It is because at low NOx optimization point HC, CO and NOx are comparatively lower than that of low PM optimization point. However, BSFC is higher in case with low NOx optimization point but it is insignificant (~1.1 percent) higher than low PM optimization point. With low NOx optimization point, PM value is also falling below the CPCB II norms (refer Table 1).

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COMBUSTION OPTIMIZATION OF 62.5 kVA GENSET ENGINE TO MEET CPCB II NORMS USING TAGUCHI METHOD

 FIGURE 9   Response graphs for BSFC and emission with

 FIGURE 10   Effect of optimized parameters on in-cylinder pressure

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proposed optimization strategies

are altered extensively during various runs. The peak pressure decreases with increased in EGR tube diameter (compare Runs 19 and 20). This can be attributed to release of reduced net energy with decrease in volumetric efficiency of the engine at higher EGR levels and owing to oxygen availability for the combustion process. Run 20 has cold EGR with higher EGR percentages compared to others hence shifting of in-cylinder pressure curve in expansion stroke. Runs 21 and 23 have similar slope with approximately same in-cylinder pressure because of having same EGR diameter and injection timing. It indicates that effect of NTP on pressure traces is insignificant. Similar observation can be made on Runs 19 and 22 (see Figure 10). EGR reduces NOx emission formation by lowering peak cylinder pressure. Because exhaust gases cannot directly enter into the combustion process, it slows down the combustion speed, as can be seen in Figure 10, by spacing oxygen and fuel molecules farther apart. Chain reactions between oxygen and fuel take longer, which results in a slower pressure rise in the cylinder. Effect of injection timing on in-cylinder pressure traces can be seen in Figure 10 (compare Runs 19 and 23). In-cylinder pressure curve of Run 19 shifts toward expansion stroke and low slope means the reaction being slow down thus indicating shifting of the combustion phase because of the retarded injection timing.

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Conclusions

Combustion Analysis Variations of in-cylinder pressure as a function of crank angle, for various optimized runs (Runs 19 to 23) are plotted in Figure 10. As shown in Figure 10, the in-cylinder pressure curves

Effects of various factors and their levels have been investigated to get optimized parameters for 62.5 kVA genset engine. Taguchi design of experiment (DOE) was chosen to select minimum numbers of experimental run to cover the whole parametric space. Effects of parameters on emissions and combustion parameter have also been studied. The following conclusions are made about the behavior of the study engine. 1. Taguchi method is useful to identify the control factors that reduce variability and move the mean to target which is achieved in this paper through two steps. © 2018 SAE International. All Rights Reserved.

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COMBUSTION OPTIMIZATION OF 62.5 kVA GENSET ENGINE TO MEET CPCB II NORMS USING TAGUCHI METHOD

2. A combination of cold EGR having 10 mm EGR tube diameter, 9 CAD bTDC injection timing, 3 mm thick copper washer for nozzle tip protrusion and 6 mm × 1.5 mm × 450 mm high pressure fuel pipe dimensions has been found optimal operating parameters. 3. As compared to other parameters, EGR (both: EGR type and percentage of EGR) had greater influence on the NOx, PM and BSFC. 4. Injection timing played a major role in HC and CO emissions. 5. The low NOx optimized point gave the most efficient result followed by low CO optimized point. This is because the present work concentrates on low NOx and low PM since other parameters are much lesser than their norms rated value. 6. Cold EGR with higher percentages slow down the reaction rates and shift pressure curve towards expansion stroke. Interaction between the selected parameters using ANOVA analysis tool can be considered as a future scope of work. Also, effect of other control parameters like injector angle, nozzle hole diameter, number of injector hole etc. can be studied in future.

References 1. Stone, R., “Introduction to Internal Combustion Engines,” (Warrendale, Society of Automotive Engineers, 1999). ISBN:0-7680-0495-0.

9

8. Brijesh, P., Chowdhury, A., and Sreedhara, S., “Effect of Ultra-Cooled EGR and Retarded Injection Timing on Low Temperature Combustion in CI Engines,” SAE Technical Paper 2013-01-0321, 2013, doi:10.4271/2013-01-0321. 9. Brijesh, P., Chowdhury, A., and Sreedhara, S., “The Simultaneous Reduction of NOx and PM Using Ultra-Cooled EGR and Retarded Injection Timing in a Diesel Engine,” International Journal of Green Energy 12(4):347-358, 2015, doi:10.1080/15435075.2013.841164. 10. Görkem, K., Adnan, P., Eyup, B., and Zafer, A., “Application of Taguchi Methods for the Optimization of Factors Affecting Engine Performance and Emission of Exhaust Gas Recirculation in Steam-Injected Diesel Engines,” Acta Polytechnica Hungarica 11(5):95-107, 2014, doi:10.12700/aph.11.05.2014.05.6. 11. Gary, W.O., “A First Course in Design and Analysis of Experiments,” (University of Minnesota, 2010), ISBN:0-71673510-5. 12. Nataraj, M., Arunachalam, V. P., and Dhandapani, N., “Optimizing Diesel Engine Parameters for Low Emissions Using Taguchi Method: Variation Risk Analysis Approach— Part I,” Indian J. Eng. Mater. Sci. 12(3):169-181, 2005. 1 3. https://www.araiindia.com/pdf/Test_Cycle_Test_Procedure. pdf, dated on 13 Sept 2017. 14. Hussain, J., Palaniradja, K., Alagumurthi, N., and Manimaran, R., “RETRACTED: Effect of Exhaust Gas Recirculation (EGR) on Performance and Emission Characteristics of a three Cylinder Direct Injection Compression Ignition Engine,” Alexandria Engineering Journal 51(4):241-247, 2012, doi:10.1016/j.aej.2012.09.004. 15. Pundir, B.P., “I. C. Engine Emission and Their Control,” (Narosa Publishing House, 2017). ISBN:978-81-8487-551-5.

2. http://www.cpcb.nic.in/divisionsofheadoffice/pci2/EmissionStandards-Diesel-engin-upto-800.pdf, dated on 9 Sept 2017.

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3. Venkat, H., Varathan, K., Kumar, K., and Rao, N., “Combustion Development to Achieve CPCB II Emission Targets with Mechanical FIE System in a 2-Valve Engine from 62.5 kVA to 160 kVA,” SAE Technical Paper 2015-260040, 2015, doi:10.4271/2015-26-0040.

17. Miles, P.C. and Andersson, O.I., “A Review of Design Considerations for Light-Duty Diesel Combustion Systems,” International Journal of Engine Research 17(1):6-15, 2015, doi:10.1177/1468087415604754.

4. Brijesh, P. and Sreedhara, S., “Exhaust Emissions and Its Control Methods in Compression Ignition Engines: A Review,” International Journal of Automotive Technology 14:195-206, 2013, doi:10.1007/s12239-013-0022-2. 5. Win, Z., Gakkhar, R.P., Jain, S.C., and Bhattacharya, M., “Investigation of Diesel Engine Operating and Injection System Parameters for Low Noise, Emissions and Fuel Consumption Using Taguchi Methods,” Proceedings of the Institution of Mechanical Engineering, Part D: Journal of Automobile Engineering 219:1237-1251, 2005, doi:10.1243/095 440705X34865. 6. Shin, B., Chun, K.M., and Lee, H., “Measurement and Simulation of Fuel Injection Pipe Pressure and Study of Its Effect on the Heat Release in a Direct Injection Diesel Engine,” KSME International Journal 11:468, 1997, doi:10.1007/BF02945085. 7. Sivaramakrishnan, K., and Ravikumar, P., “Performance Optimization of Karanja Biodiesel Engine Using Taguchi Approach and Multiple Regressions,” ARPN Journal of Engineering in Applied Science 7(4):506-516, 2012, ISSN:1819-6608. © 2018 SAE International. All Rights Reserved.

18. Luo, F.Wang, C. ,Xue, F. ,Ye, B., et al., “A Study on the Influence of Fuel Pipe on Fuel Injection Characteristics of Each Nozzle Hole in Diesel Injector,” MATEC Web of Conferences, 40, 2016, doi:10.1051/matecconf/20164002016.

Contact Information Victor Debnath-Engine Design Escorts Agri Machinery Knowledge Management Centre | 15/5, Mathura Road, Faridabad Mo. No.: +91-9830553224 [email protected]

Acknowledgments Authors would like to acknowledge Mr. Punit Bhardwaj, Deputy General Manager (Engine Design) Escorts LTD. for granting permission to publish this work. And special thanks to Mr. A. C. Vignesh, Asst. Manager (Engine Design) Escorts LTD. for his extreme support to this work.

Downloaded from SAE International by Victor Debnath, Wednesday, April 18, 2018 10 COMBUSTION OPTIMIZATION OF 62.5 kVA GENSET ENGINE TO MEET CPCB II NORMS USING TAGUCHI METHOD

Definitions/Abbreviations ACS - Air Conditioning Specialist ANOVA - Analysis of Variance BHP - Brake Horse Power BSFC - Brake Specific Fuel Consumption bTDC - Before Top Dead Center CAD - Crank Angle Degree CDM - Crank Detection Module CO - Carbon Monoxide CPCB - Central Pollution Control Board DI - Direct Injection DOE - Design of Experiments

EGR - Exhaust Gas Recirculation GHG - Green House Gases HC - Hydrocarbon HCLD - High Complexity Laboratory Director HFIR - High Flux Isotope Reactor HPFP - High Pressure Fuel Pipe NDIR - Non-dispersive Infra-Red NOx - Oxides of Nitrogen NTP - Nozzle Tip Protrusion OA - Orthogonal Array PM - Particulate Matter SN Ratio - Signal to Noise Ratio

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