Journal of Natural Gas Science and Engineering 21 (2014) 524e531
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Application of GreyeTaguchi based multi-objective optimization strategy to calibrate the PMeNHCeBSFC trade-off characteristics of a CRDI assisted CNG dual-fuel engine Sumit Roy*, Ajoy Kumar Das, Rahul Banerjee Department of Mechanical Engineering, NIT Agartala, Tripura, India
a r t i c l e i n f o
a b s t r a c t
Article history: Received 4 August 2014 Received in revised form 13 September 2014 Accepted 15 September 2014 Available online 3 October 2014
The present work attempts to simultaneously reduce the BSFCeq, NHC and PM emissions of a CRDI assisted diesel engine under CNG-diesel dual-fuel mode. Load, fuel injection pressure and CNG energy share were chosen as input parameters with NHC, PM and BSFCeq as the response variables. To reduce the experimental effort the experiments have been performed by employing Taguchi's L16 orthogonal array. In order to search for the optimal process response, the Grey relational analysis is employed for solving the optimization problem. The optimal combination of the input parameters was obtained using the Grey relational grade and signal-to-noise ratio as a performance index, which achieved the desired response characteristics. The optimal combination so obtained was further confirmed through experimentation. Among the three, load was found to be the most influencing factor. © 2014 Elsevier B.V. All rights reserved.
Keywords: CRDI CNG Grey relational analysis Taguchi method
1. Introduction Diesel engine based technology in the present millennium has undergone a paradigm shift in its perspectives to meet the increasingly stricter emission directives on one hand and consumer expectations of superior fuel economy on the other. Such a state of responsiveness to the present day requirements is necessitating an unprecedented increase of dependence on control of the several new degrees of freedom that are being called into play simultaneously by virtue of the significant increases in the mechanical and electronic complexity of engine hardware and after treatment systems dictated by the incorporation of new technologies such as VVT, VGT, CRDI, GDI, VIS, exhaust after-treatment add-ons of SCR, DPF etc. together with the shift towards newer and innovative low temperature combustion technology concepts such as HCCI
Abbreviations: BDO, baseline diesel operation; BP, brake power; BSFCeq, brake specific fuel consumption equivalent; BTDC, before top dead centre; CI, compression ignition; CNG, compressed natural gas; CRDI, common rail diesel injection; DI, direct injection; FIP, fuel injection pressure; GRG, Grey relational grade; HC, hydrocarbon; IC engine, internal combustion engine; NOx, oxides of nitrogen; PM, particulate matter; ppm, parts per million. * Corresponding author. Tel.: þ91 9402108135; fax: þ91 3812346360. E-mail addresses:
[email protected],
[email protected] (S. Roy). http://dx.doi.org/10.1016/j.jngse.2014.09.022 1875-5100/© 2014 Elsevier B.V. All rights reserved.
(Homogeneous Charge Compression Ignition), DCCS (Dilution Controlled Combustion System), HPLI (Highly Premixed Late Injection), HCLI (Homogeneous Charge Late Injection), Premixed Charge Compression Ignition (PCCI) and Reactivity Controlled Compression Ignition (RCCI) offer the promise of improved engine efficiencies along with markedly reduced emission footprints from conventional engines (McGeehan et al., 2005; Johnson, 2008, 2010, 2011; Zhao, 2010). Common Rail Diesel Injection systems have led the technological renaissance (Badami et al., 1999; Suh, 2011) in diesel injection characteristics of the present day due to its efficacy in drastically reducing BSFC and the conventional PM emission precursors as compared to conventional diesel operation (Balusamy and Marappan, 2010; Nagata et al., 2004; Shimazaki et al., 2003; Pickett and Siebers, 2004; Minato et al., 2005). That said the very ability of the CRDI systems to decrease PM emissions has been found to be a penalizing precursor for NOx formation which have been observed to paradoxically increase (Badami et al., 1999; Desantes et al., 2004; Pierpont and Reitz, 1995; Payri et al., 2006) on account of higher peak temperature arising out of very lean and homogenous conditions which provide impetus for attaining close-to adiabatic flame temperatures during the ensuing combustion. To contain the consequence of NOx emissions while retaining the incentives of lower PM and fuel consumption on CRDI systems, EGR (Reitz, 1998; Ladommatos et al., 1998; Hountalas
S. Roy et al. / Journal of Natural Gas Science and Engineering 21 (2014) 524e531
et al., 2008; Maiboom et al., 2008; Roy et al., 2014a; Bose et al., 2013) and pilot injection strategies (Buyukkaya and Cerit, 2008; Thurnheer et al., 2011) have been widely investigated. Comparing the context of the present day insecurities of convention fossil fuel based energy resources, air pollution, and climate change that are collectively calling into question the fundamental sustainability of the current energy system, alternative fuels, are destined to be a dominant stake holder in the transition of the energy sector in the immediate future. Of all the existing alternative fuel resources, CNG with its inherent synergy of its cheap availability and its projected sustainability till the immediate future (Kvenvolden, 1994; Dyntar et al., 2002) along with its potential of reducing the regulated emission footprint of conventional IC engines (Fritz and Egbuonu, 1992; Carlucci et al., 2008; Kusaka et al., 2000; Cascetta et al., 2008; Maji et al., 2008; Kalam and Masjuki, 2011; Liu et al., 2013), provides itself as a desirable and potent/alternative energy transition vector to the ultimate hydrogen based economy. It is thus apparent from the discussion that the PMeNOxeBSFC trade-off problem requires increased design space to explore the possibility of obtaining possible solutions to satisfy the conflicting objectives. Such extended design space is provided by the increase in control/design variables which can be suitably explored for attaining the desired objectives. That said, increase of parametric variability on conventional diesel platforms as provided by the CRDI and CNG dual-fuel systems needs to be suitably attuned to obtain the desired optimal responses. Though a full factorial approach would have been the ideal methodology to explore the entire design space with one at a time variation of the input variables, such efforts are constrained by the penalty of unviable experimental cost and time. Thus a methodology is needed to be adopted wherein the optimal exploration of the design space can be performed with reduced yet experimentation. To this end the Taguchi methodology provides an effective and established (Saravanan et al., 2010, 2013; Wu and Wu, 2013; Lee et al., 2013; Ganapathy et al., 2009) statistical tool derived from the theory of design of experimentation. Though, the Taguchi platform has been utilized as a very popular process optimization technique, it has been observed to be unsuitable to solve multi-objective optimization problems (MOOPs) (Tarng and Yang, 1998; Ross, 1988). To overcome this limitation, Grey relation analysis (GRA) theory has been employed successfully in conjunction with the Taguchi method (Datta et al., 2008; Tarng et al., 2000) to solve the MOOPs in diverse engineering domains including the IC engine paradigm (Pohit and Misra, 2013; Karnwal et al., 2011). The main objective of the present work was to find an optimal combination of load, fuel injection pressure (FIP) and CNG energy share (CES) for the simultaneous reduction of BSFCeq, NHC (NOx þ HC) and PM emissions. 2. Instrumentation The experiment was conducted on an existing single cylinder four-stroke CI engine coupled to a Common Rail Direct Fuel Injection system as detailed in Table 1. The engine was coupled to an aircooled eddy current dynamometer of PowerMag® make. The CRDI setup is an attachment to the experimental engine. It consists of a high-pressure fuel pump, rail, high-pressure fuel injector and the heart of the system being the electronic injection controller (EIC). The description of the fuel injection system is given in Table 2. The CNG was stored in a 25 lit cylinder compressed at 210 bar. The CNG was inducted into the Vidhata make VL-8 single cylinder four stroke diesel engine through the manifold of the engine intake. An open loop Electronic Control Unit (OPECU) was provided with the CNG manifold injection kit to decide the injection start angle and
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Table 1 Experimental engine specification. Specification
Resources
Make No of cylinder Bore Stroke Displacement Cooling Compression ratio
Vidhata One (1) 120 mm 139.7 mm 1580 cc Water 18:1
Valve timing Exhaust valve opening Exhaust valve closing Inlet valve opening Inlet valve closing
35 before BDC 4 after TDC 4 before TDC 35 after BDC
the induction duration. Technical Specification CNG Injector Rail is given in Table 3. The CNG energy share was calculated as per Equation (1) (Roy et al., 2014c). The exhaust gases were sampled by a 5 Gas analyzer and an AVL smoke meter (415S) was used to measure the soot content, present in the exhaust. The specifications of the emission measuring apparatus are detailed in Tables 4 and 5. The layout of the experimental setup used to conduct the experiments is shown in Fig. 1.
CESi ¼
ðm_ D ÞBD LHVD i ðm_ D ÞDual LHVD i ðm_ D ÞBD LHVD i
(1)
2.1. Methodology In the present experimental work, the fuel injection methodology was undertaken for 25%, 50%, 75% and full load characteristics of the engine. The experimental engine when subjected to progressive higher loads then demanded a higher injection rail pressure. Consequently for each variation of injection duration at the given load, the injection rail pressure would adjust automatically as per the specification of the CRDI setup to maintain the constant speed set. The initial injection duration for each load was set to approximately 225 bar which was the designed fuel nozzle opening pressure of the experimental engine. The start of injection angle was set to 5 BTDC for all the cases. The injection duration on the CRDI platform for each load was then reduced at particular intervals specific to each case of loading. Such reduction of injection duration was accompanied by a complementary increase of pressure needed to maintain the set constant speed of 800 rpm. The reduction in fuel injection duration was continued in steps until a minimum injection duration was reached at that given load, beyond which the stability of engine operation was compromised. The effect of drastic increase in FIP has been observed to stimulate a significant reduction in the spray droplet diameter distribution of the injected fuel due to better atomization characteristics obtained due to the drastic increase in the pressure drop experienced by the liquid fuel during injection. This enhances a better Table 2 Specification of the fuel injector. Specification
Resources
Type
Common rail injection system Bosch 10e120 MPa 5 (Symmetric) 0.15 mm 120
Make Injection pressure Number of holes Nozzle diameter Injection angle
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S. Roy et al. / Journal of Natural Gas Science and Engineering 21 (2014) 524e531 Table 3 Technical specification CNG injector rail.
Table 5 AVL 415S specifications.
Make
VALTEK
Piloting type Max working pressure Burst pressure Opening time Closing time Valve seat diameter
PEAK and HOLD 0.45 MPa Over 10 MPa 3.3 ms 2.2 ms 4.0.mm
Measurement principle Measured value output Measurement range Detection limit Resolution Interfaces Sample flow Ambient conditions
penetration profile of the liquid fuel jet in the cylinder enabling rapid vaporization of the inducted fuel which in turn promotes superior fueleair mixing characteristics and reduce the BDO ignition delay period considerably, all of which provide the precursors to faster rates of combustion characterized by high ROHR at the onset of combustion, significant increase in peak temperatures of the burning gases and reduced residence time-factors that collectively inhibit formation and agglomeration of particulates and substantially reduces the PM and TUHC emission profile during the CRDI operation paradigms. That said, the fact that the diesel engine operates un-throttled, reductions in the FID at a given load step inducts a progressively lower quantity of fuel per cycle promoting improved BSFC and BTE profiles but at the expense of inducing very lean equivalence ratios under which combustion is initiated. Combined with higher ROHR and peak combustion temperature, such lean equivalence ratios provide an ideal backdrop for a significant increase in NOx emissions. Thus a potential design space of experimentation is provided wherein the benefits of reduced PM emissions and BSFC footprint of a conventional diesel engine is challenged by the necessity of reducing its NOx emission footprint.
2.2. Experimental uncertainty analysis The uncertainty expected during the sampling of the experimental parameters by the corresponding components of engine and emission analysis instrumentation is enlisted in Tables 4 and 5, Tables A1 and A2 in Appendix A, as declared by their respective manufacturers. Root mean square method was used to analyse the combined uncertainty for the performance parameters (Roy et al., 2014a,b; Rakopoulos et al., 2010) and its calculation has been detailed in Table A3 in Appendix A. Each recorded value for a given case of engine operation (with & without CNG) was the average value of six (6) repeated observations over a sampling time of 2 minutes. Total Sampling Uncertainty (TSU) of each observation set at each case of engine operation was calculated. The sampling uncertainty of the emission analyser for
Repeatability Reproducibility
Measurement of filter paper blackening FSN (filter smoke number) or mg/m3 (soot concentration) 0e10 FSN 0.002 FSN or ~0.02 mg/m3 0.001 FSN or 0.01 mg/m3 2 serial RS232 interfaces with AK protocol ~10 l/min 5e55 C/max.95 RH; without condensationSea level 500 to þ5000 m Standard deviation 1s ¼ ±(0.005 FSN þ 3% of the measured value @ 10 s intake time) s ±(0.005 FSN þ 6% measured value)
each of the respective pollutants and the relative range of the consecutive observations were taken into account. An example calculation of the same for a particular case of engine operation has been detailed in Table A4 in Appendix A. For a credible viewpoint of the uncertainty analysis, the additional index of standard deviation of the consecutive samplings has been calculated at each of the designated engine operating conditions. The average standard deviation and the average TSU over the entire scope of experimentation have been reported in Table A5 in Appendix A. The specification of the fuels used is detailed in Tables A6 and A7 in Appendix 1. 3. Design of experiment (DoE) As outlined by Broge (2009), the large number of parameters that affect emissions and combustion characteristics requires a complex calibration process, which could generate a seemingly infinite number of experimental conditions to evaluate. The designof-experiment (DoE) is a statistical technique that is adopted to streamline and reduce the number of test cases within viable limits, which can then be conducted to ascertain the desired experimental responses. Such endeavours reduce the cost and time resource footprint as compared to a full factorial experimental approach. DoE analysis technique is utilized in evaluating experimental responses of a physical system that is known to be affected by numerous factors and their interactions. In a design of experiment technique, the response variables are an unknown function of the process variables, which are known as design factors. DoE starts with identifying the input variables and the response (output) that is to be measured. For each input variable, a number of levels are defined that spans over the range for which the effect of that variable is desired to be known. The approach has been often used in IC
Table 4 5 Gas analyzer specifications (AVL DIGAS 444). Measured parameter
Measuring range
Resolution
Accuracy
Carbon monoxide (CO)
0e10% vol
0.01% vol
