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Applied Thermal Engineering 31 (2011) 2247e2253

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Applied Thermal Engineering

journal homepage: www.elsevier .com/locate/apthermeng

Effect of exhaust gas recirculation on the cycle-to-cycle variationsin a natural gas spark ignition engine

Asok K. Sen a,*, Sudhir K. Ash b, Bin Huang c, Zuohua Huang c

aRichard G. Lugar Center for Renewable Energy and Department of Mathematical Sciences, Indiana University, 402 N. Blackford Street, Indianapolis, IN 46202, USAbDepartment of Chemistry, B. B. College, Burdwan University, Asansol, Indiac State Key Laboratory of Multiphase Flow in Power Engineering, School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China

a r t i c l e i n f o

Article history:Received 13 December 2010Accepted 15 March 2011Available online 2 April 2011

Keywords:Natural gasCycle-to-cycle variationsSpark ignition engineExhaust gas recirculationWavelet analysis

* Corresponding author. Tel.: þ1 317 274 6922; faxE-mail address: asen@iupui.edu (A.K. Sen).

1359-4311/$ e see front matter � 2011 Elsevier Ltd.doi:10.1016/j.applthermaleng.2011.03.018

a b s t r a c t

This study investigates the effect of exhaust gas recirculation (EGR) on the cycle-to-cycle variations (CCV)in combustion in a natural gas spark ignition engine. The engine is operated at 2000 rpm and a stoi-chiometric fuel-air mixture is used. The EGR level is changed from 0% to 5%, 10%, 15%, and 20%. For eachEGR level, a continuous wavelet transform is used to analyze the time series of the indicated meaneffective pressure (IMEP) over 200 cycles. The dominant oscillatory modes of the CCV are identified andthe engine cycles over which these modes may persist are delineated. The results reveal that the CCV ofthe IMEP occur on multiple timescales and exhibit complex dynamics. With no EGR, mainly highfrequency intermittent fluctuations are observed. As the EGR level is increased, more persistent lowfrequency variations tend to develop. In addition, the spectral power increased with an increase in theEGR level. At the EGR level of 20%, the spectral power is found to increase significantly indicating thatEGR has a pronounced effect on increasing the CCV. Knowledge of the dominant modes of variability maybe useful to develop effective control strategies for reducing the CCV and improving engine performancein the presence of EGR.

� 2011 Elsevier Ltd. All rights reserved.

1. Introduction

Internal combustion engines running on conventional fuels suchas gasoline or diesel often emit undesirable amounts of NOx, CO,and unburned hydrocarbons (UHC) into the atmosphere. In order toregulate environmental pollution, higher emission standards arebeing continually imposed on vehicles that are operated in theUnited States and many other countries around the world. To meetthese emission standards, alternative fuels such as natural gas andbiodiesel are currently being used [1e5]. The main constituent ofnatural gas is methane, which has the lowest carbon to hydrogen(C/H) ratio compared to other hydrocarbon fuels, making naturalgas one of the cleanest fuels available today. Because of low C/Hratio of methane, a natural gas engine produces less CO and UHCemissions than a gasoline or a diesel engine [6e9]. In order toachieve low NOx emissions, a natural gas engine needs to beoperated with ultra lean mixtures. However, the lean burn strategyreduces the thermal efficiency of the engine, and also tends toincrease CO and UHC emissions. Therefore, depending on the

: þ1 317 274 3460.

All rights reserved.

air-fuel ratio in the combustible mixture, there is a trade-offbetween thermal efficiency and exhaust emissions. An alternateway of reducing NOx emissions is to retard spark timing, but thishas also been found to decrease thermal efficiency and increaseUHC emissions. In the 1970s, the three-way catalyst (TWC) tech-nology was developed to reduce exhaust emissions. In fact, theTWC technology can reduce NOx, CO and UHC emissions, but itworks most efficiently with a stoichiometric mixture. When theengine operates with a near-stoichiometric mixture, the thermalefficiency is improved, but the in-cylinder temperature increases;consequently, the thermal stresses and knocking tendency increase[10].

NOx is formed in high concentrations when the in-cylindertemperature exceeds about 2500 �F. The in-cylinder temperaturecan be reduced by recycling part of the exhaust gases into theengine cylinders. This process is referred to as exhaust gas recir-culation (EGR). There are two ways in which EGR can be imple-mented. External EGR is achieved by connecting a pipe from theexhaust to the intake manifold, with the flow of exhaust gasesregulated by a control valve. Internal EGR is achieved when thevalve timing is arranged so that there is some backflow into thecombustion chamber from the exhaust, or all of the exhaust gasesare not expelled from the combustion chamber during the exhaust

A.K. Sen et al. / Applied Thermal Engineering 31 (2011) 2247e22532248

stroke. Engines with internal EGR must have variable valve timing,and EGR is achieved by increasing the valve overlap. While internalEGR does not require a connecting pipe and a valve, a majoradvantage of external EGR is that the exhaust gases can be cooledbefore being fed back into the intake manifold, thus providingbetter control on the in-cylinder temperature. This is referred to ascooled EGR [11].

In a spark ignition (SI) engine, the recirculated inert exhaustgases displace some of the intake charge, thereby reducing thecombustion temperature and NOx formation. In a diesel engine, theinert exhaust gases replace some of the excess oxygen in the pre-combustion mixture. Typically, about 5e20% of the exhaust gasesare fed back into the intake manifold as EGR in an SI engine.Excessive EGR level may lead to misfires. The effect of EGR onengine performance and exhaust emissions has been investigatedby several researchers [12e40]. These studies have been performedin spark ignition (SI) engines, compression ignition (CI) engines,and homogeneous charge compression ignition (HCCI) engines.Some studies have also used nitrogen or CO2 to simulate EGR[41,42]. Collectively, these investigations establish the role of EGR inreducing NOx emissions. However, some of these studies havereported an increase in the cycle-to-cycle combustion variationsdue to EGR, which are discussed below.

As noted in [10], using EGR with a stoichiometric inlet mixturewill lead to a decrease in in-cylinder temperature and a decrease inknocking tendency; it would permit the engine to use turbo-charging, relatively high compression ratio, and optimum sparkadvance timing to achieve a relatively higher thermal efficiency,compared to a stoichiometric mixture without EGR. In addition,adding EGR to the inlet mixture will reduce the oxygen partialpressure in the mixture, and consequently, the in-cylinder NOxformation will decrease. Furthermore, when EGR is added toa stoichiometric mixture, the use of TWC for necessary emissionreduction is also possible [10].

It is well known that the process variables such as pressure in aninternal combustion engine undergo cycle-to-cycle variations(CCV) [43,44]. Cycle-to-cycle variations have been observed in SI, CIand HCCI engines [45e50]. In particular, the CCV have been studiedextensively in natural gas engines under different operating

Fig. 1. Schematic diagram of the experimental set up. 1-fuel tank, 2-fuel pump, 3-fuel filter,9-gas mixer, 10-CNGeH2 control step motor, 11-CNGeH2 regulator, 12-CNGeH2 valve, 13-csensor, 18-coolant water temperature sensor, 19-crankshaft position sensor, 20-oxygen sencontrol unit.

conditions [51e58]. The CCV may reduce the power output of theengine, lead to operational instabilities, and result in undesirableengine vibrations and noise. It has been estimated that eliminationof the CCV may result in about 10% increase in power output for thesame fuel consumption in a gasoline engine [50].

There have been a few studies on investigating the effect of EGRon the CCV. For example, Fujikawa et al. [59], and Koike and Suzuki[60] examined the CCV in a gasoline engine, and Huang et al. [61]studied the CCV in a natural gas engine, with EGR. In their work,Huang et al. [61] used a spark ignition engine fueled by a stoichio-metric mixture, and analyzed the time series of the indicated meaneffective pressure (IMEP). Use of a stoichiometric mixture isappropriate because with many EGR systems, a three-way catalystis used for after-treatment of the exhaust gases, and as mentionedbefore, this three-way catalyst works most efficiently with a stoi-chiometric mixture. Huang et al. [61] found that as the EGR levelwas increased, the CCV of the IMEP time series also increased. Theiranalysis was based on the coefficient of variation (COV) of the IMEPtime series.

For a time series fxig, i ¼ 1, 2, 3, ., N, the COV is defined as theratio of its standard deviation ðsÞ to its mean value ðmÞ, and isusually expressed in percent form.

COV ¼ s

m� 100% (1)

where

m ¼ 1N

XNi¼1

xi; s ¼"1N

XNi¼1

ðxi � mÞ2#1=2

(2)

The coefficient of variation (COV) is a useful statistic forcomparing the degree of variation between two time series evenwhen their mean values are quite different from each other. Fora given time series, the COV provides a single overall numericalmeasure characterizing the temporal variability in the data;however, it does not take into account the spectral characteristics ofthe time series. The objective of this paper is to use awavelet-basedspectral-temporal approach to describe the CCV of the IMEP timeseries, and to estimate the effect of EGR on the CCV.

4-ignition coil, 5-distributor, 6-spark plug, 7-fuel injector, 8-manifold pressure sensor,oolant in, 14-coolant out, 15-air filter, 16-idling control step motor, 17-throttle positionsor, 21-battery, 22-ignition switch, 23-gasoline/CNG selection switch, ECU-electronic

Fig. 2. (a) Schematic diagram and (b) photograph of the exhaust gas recirculationsystem (EGR) system.

Table 1Engine specifications.

Engine type HH368Q gasoline engine

Displacement (ml) 796Bore (mm) 68.5Stroke (mm) 72Compression ratio 9.4Ignition sequence 1e3e2Rated speed (rpm) 5500Rate power (kW) 26.5

Table 2Composition of natural gas.

Constituent CH4 C2H6 C3H8 N2 CO2 Others

Volume fraction (%) 96.16 1.096 0.136 0.001 2.540 0.067

A.K. Sen et al. / Applied Thermal Engineering 31 (2011) 2247e2253 2249

Wavelet-based techniques are being increasingly used for timeseries analysis in a wide variety of applications. They are particu-larly useful for the analysis of transient and intermittent processes.Wavelet analysis is performed using either (a) continuous wavelettransform (CWT), or (b) discretewavelet transform (DWT) [62]. TheCWT is typically used for feature extraction of a time series. TheCWTmaps the spectral characteristics of a time series on to a time-frequency (time-period) plane fromwhich the various periodicitiesand their temporal variations, if any, can be discerned by visualinspection. Using a variable-size window in the time-frequency(time-period) plane, the CWT adjusts the time and frequencyresolutions in an adaptive fashion. It uses a window that narrowswhen focusing on high-frequency components of the time seriesand widens on low-frequency features, analogous to a zoom lens[63]. Recently, wavelet analysis using CWT has been applied to theanalysis of CCV in internal combustion engines in the papers by Senet al. [48,49,57,58].

In this paper we use CWT to examine the IMEP time seriesacquired by Huang et al. [34], and elucidate the spectral-temporalcharacteristics of their CCV. In particular, by calculating thewavelet power spectrum (WPS) and the global wavelet spectrum(GWS), the dominant oscillatory modes of the CCV are identified,and the engine cycles over which these modes may persist aredelineated. On the basis of the dominant periodicities and spectral

power, we investigate the effect of EGR on the CCV of the IMEP ina natural gas spark ignition engine.

2. Experimental procedure

The natural gas engine used in this study was modified from anHH368Q gasoline engine. A schematic diagram of the experimentalset up is shown in Fig. 1, and the EGR system is depicted in Fig. 2.The specifications of the engine are listed in Table 1, and thecomposition of the natural gas used in the experiment is given inTable 2. The engine was operated at 2000 rpm, with a stoichio-metric fuel-air mixture, and wide open throttle (WOT). The excessair ratio was monitored by a Horiba MEXA700l instrument witha measuring accuracy of 5%. An electronic control unit was used tocontrol the ignition timing. The experiments were conducted withoptimum ignition timing which was regulated to the level at whichthe engine has the maximum brake torque (MBT). A cooled EGRsystemwas used in the experiment. After passing through the EGRcooler and the EGR valve, the exhaust gas entered the intakemanifold and mixed with the fresh fuel-air mixture, Different EGRratios could be set by adjusting the EGR valve. The flow rate of theEGR coolant was maintained constant during the test. An ECMEGR5230 analyzer with a measuring accuracy of 0.5% was used tomonitor the EGR ratio. The engine speed, fuel-air ratio, and throttlesetting were all held constant throughout the data collectionperiod. The EGR ratio is defined by the formula: % EGR ¼ [VEGR/(V1þ VEGR)]�100, where VEGR is the volume flow rate of EGR, and V1is the volume flow rate of the intake fuel-air mixture. The atmo-spheric conditions in the laboratory changed a little after the test. Inparticular, the temperature increased by 2.5 �C from 24 �C, pressuredecreased by 0.13 kPa from 97.4 kPa, and the relative humiditydecreased by 3.7% from 62%.

The in-cylinder pressure was measured by means of a Kistler6117BF17 piezoelectric pressure transducer with a sensitivity of15 pC/bar and a resolution of 10 Pa, and the dynamic top deadcenter was determined by motoring calibration. The pressuresignal was recorded for every 0.1� of the crank angle. The crankangle signal was acquired with a Kistler 2613B crank angleencoder, and the pressure and crank angle information wererecorded by a Yokogawa DL750 data acquisition system. Thepressure measurements were made for 200 consecutive enginecycles. From the pressure measurements, the IMEP values werecalculated. Note that IMEP is the average pressure in the cylinderover one engine cycle:

IMEP ¼ WC=Vd; (3)

Fig. 3. IMEP time series of the natural gas spark engine with EGR levels of (a) 0%, (b) 5%, (c) 10%, (d) 15%, and (e) 20%. The engine speed is 2000 rpm and a stoichiometric fuel-airmixture is used.

A.K. Sen et al. / Applied Thermal Engineering 31 (2011) 2247e22532250

where Vd is the engine displacement volume, andWC is the amountof work done per cycle given by

Wc ¼I

PdV ; (4)

P being the actual (i.e., measured) pressure in the cylinder. In ourexperiment, the EGR level was changed from 0% to 5%, 10%, 15% and20%.

3. Wavelet analysis and results

As mentioned above, we analyzed the IMEP time series fora natural gas spark ignition engine with EGR, using a continuouswavelet transform (CWT). The wavelet analysis methodology usingCWT is described in [64]. We summarize the main steps below. Amother wavelet is chosen and its convolution with the time seriessignal is computed. This convolution is defined as the CWT of thetime series. The CWT is computed by manipulating the motherwavelet over the time series in two ways: it is moved to variouslocations on the time series, and it is stretched or squeezed. If thewavelet locally matches the shape of the time series, then a largetransform value is obtained. If, on the other hand, the wavelet andthe time series do not correlate well, a low value of the transform

will result [64]. The squared modulus of the CWT, representing thesignal energy, is defined as the wavelet power spectrum (WPS). TheWPS is plotted on a time-frequency (or time-period) plane, whichdepicts the various periodicities of the time series and theirtemporal variations. For the IMEP time series considered here, theWPS is plotted on a plane with the cycle number and period (cycle)as the two axes. From the WPS, another useful quantity called theglobal wavelet spectrum (GWS) can be computed. The GWS is theaverage of the WPS overall time, and is analogous to a smoothedFourier spectrum. From the locations of the peaks in the GWS, thedominant periodicities of the time series can be identified. In ouranalysis, we used a Morlet wavelet of order 6 as the motherwavelet. The choice of order 6 provides a good balance between thetime and frequency resolutions. The Morlet wavelet has been usedas a mother wavelet in a variety of applications. The interestedreader is referred to [64] for details.

Fig. 3 depicts the IMEP time series of the natural gas sparkignition engine with 0%, 5%, 10%, 15% and 20% EGR. The waveletpower spectrum (WPS) and the global wavelet spectrum (GWS) ofeach of these time series are depicted in Fig. 4. The contour lines inthe WPS enclose regions with greater than 95% confidence withrespect to a red-noise background spectrum, and the area belowthe U-shaped curve represents the cone of influence (COI). For thecomputation of the WPS, the time series is padded with zeros at

Fig. 4. (a) Wavelet power spectrum (WPS) and global wavelet spectrum (GWS) of theIMEP time series shown in Fig. 3(a) for the natural gas spark ignition enginewith no EGR.(b)Wavelet power spectrum (WPS) and globalwavelet spectrum (GWS)of the IMEP timeseries shown in Fig. 3(b) for the natural gas spark ignition engine with 5% EGR. (c)Wavelet power spectrum (WPS) and global wavelet spectrum (GWS) of the IMEP timeseries shown in Fig. 3(c) for the natural gas spark ignition engine with 10% EGR. (d)Wavelet power spectrum (WPS) and global wavelet spectrum (GWS) of the IMEP timeseries shown in Fig. 3(d) for the natural gas spark ignition engine with 15% EGR. (e)Wavelet power spectrum (WPS) and global wavelet spectrum (GWS) of the IMEP timeseries shown in Fig. 3(e) for the natural gas spark ignition engine with 20% EGR.

A.K. Sen et al. / Applied Thermal Engineering 31 (2011) 2247e2253 2251

both ends. The zero padding leads to edge effects which make theWPS inside the COI unreliable; the WPS inside the COI shouldtherefore be used with caution [64].

Based on the record length of 200 cycles of the IMEP time series,we confine our considerations to periodicities of less than 32-cycle.It is clear from theWPS and GWS illustrated in Fig. 4 that the cycle-to-cycle variations of the IMEP occur at multiple timescales. Inparticular, Fig. 4(a) shows that, in the absence of EGR, the CCVexhibit mainly high frequency intermittent fluctuations. As EGR isintroduced, persistent low frequency oscillations tend to develop inthe CCV [see Fig. 4(bee)]. For example, as seen in Fig. 4(c), withEGR¼ 15%, there is strong power around the 16-cycle period whichpersists approximately over 60 engine cycles.When the EGR level isincreased to 20%, we see from Fig. 4(e) that there is persistentoscillation around the 8-cycle period lasting over almost 60 enginecycles. In addition, it can be seen from the GWS plots for differentEGR levels that the spectral power increases as the EGR levelincreases. When the EGR level is increased beyond 10%, there isa remarkable increase in the overall spectral power. A comparisonof the GWS in Fig. 4(a) and (e) shows that when EGR ¼ 20%, theoverall spectral power has increasedmore than 500 times from thatwithout EGR, indicating that EGR has a pronounced effect onincreasing the CCV of the IMEP.

As mentioned in the Introduction, Huang et al. [61] analyzed theCCV of the IMEP time series examined here, using the coefficient ofvariation (COV). They found that as the EGR level increased, the COVvalues also increased, thus concluding that EGR increases the cyclicvariability of the IMEP. These results are consistent with thoseobtained in this study based on the global wavelet spectrum (GWS)of the IMEP time series. From their analysis using COV, Huang et al.[61] also found that as the EGR level increased beyond 10%, therewas a remarkable increase in the COV, implying that at higher EGRlevels, the effect of EGR is more pronounced. The same trend isfound from the GWS in Fig. 4. An additional advantage of thewavelet analysis is that it can clearly reveal the spectral charac-teristics of the IMEP time series. In other words, it can describe theirmultiscale dynamics consisting of high frequency intermittentfluctuations and low frequency persistent variations which prevaildepending on the EGR level.

4. Concluding remarks

We have analyzed the cycle-to-cycle variations (CCV) of theindicated mean effective pressure (IMEP) in a natural gas sparkignition engine with EGR. Using a continuous wavelet transform(CWT), we have identified the dominant periodicities in the IMEPtime series and delineated the engine cycles over which theseperiodicities may persist. Our results indicate that in the absence ofEGR, the CCV exhibit mainly high frequency intermittent fluctua-tions. As EGR level is increased, persistent low frequency variationstend to develop. We have also assessed the effect of EGR on the CCVby means of the spectral power derived from the global waveletspectrum (GWS). At the EGR level of 20%, the spectral power isfound to increase significantly from that with no EGR, indicatingthat EGR has a pronounced effect on increasing the CCV. Knowledgeof the dominant modes of variability may be useful to developeffective control strategies for reducing the CCV and improvingengine performance.

Due to limited record length of 200 cycles, we restricted ourconsideration to periodicities less than 32-cycle. By conductingexperiments over a larger number of engine cycles and analyzingthe data, it would be possible to detect the presence of lowerfrequencies or long-term variations in the CCV. A longer recordlengthwill also enable us to determine if the periodicities identifiedherewill persist over a longer time interval, i.e., more engine cycles.

A.K. Sen et al. / Applied Thermal Engineering 31 (2011) 2247e22532252

These experiments are currently in progress, and the results will bereported in a future publication.

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