Diesel engine performance and exhaust emission analysis using waste cooking biodiesel fuel with an artificial neural network

Ghobadian, Barat; Rahimi, Hadi; Nikbakht, Ali; Najafi, G.; Yusaf, Talal

doi:10.1016/j.renene.2008.08.008

Cited by 451 publications

(205 citation statements)

References 27 publications

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“…B50 soybean biodiesel has slightly over a 50% reduction in CO emissions. The lower CO reading for the different biodiesels could be attributed to biodiesel having higher oxygen content [65,66]. A higher oxygen content results in more complete combustion and less CO emission in the exhaust.…”

Section: Carbon Monoxide (Co) Emissionmentioning

confidence: 96%

Comparative study of diesel engine performance and emission with soybean and waste oil biodiesel fuels

Azad¹,

Rasul²,

Giannangelo³

et al. 2015

Int. J. Automot. Mech. Eng.

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The study investigated the engine performance and emission using biodiesel from soybean oil and waste cooking oil. The fuel properties of these biodiesels were determined using ASTM D6751and EN 14214 standards. The fuels were tested in a multi-cylinder diesel engine with an electromagnetic dynamometer and a 5-gas analyser was used for emission analysis. The result shows that the thermal performance of the engine slightly decreases with increase of the biodiesel blends ratio (i.e. B5, B10, B15, B20 and B50). On the other hand, emission decreases with the increase of biodiesel blends. The reduction in emissions was different for both biodiesels. Waste oil biodiesel showed better trends of emissions reduction with increase of the biodiesel percentage compared with soybean biodiesel. The brake specific fuel consumption (BSFC) of both biodiesels is (6.05%, 9.13%, 12.36% and 18.57% for soybean) and (8.17%, 11.40%, 17.71% and 14.96% for waste cooking oil) higher than diesel, respectively. However, soybean biodiesel consumed less fuel and produced more power and torque compared to waste oil biodiesel. The study concluded that B10 soybean biodiesel blend produced more consistent and expected results than waste oil biodiesel from the performance and emission point of view.

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Section: Carbon Monoxide (Co) Emissionmentioning

confidence: 96%

Comparative study of diesel engine performance and emission with soybean and waste oil biodiesel fuels

Azad¹,

Rasul²,

Giannangelo³

et al. 2015

Int. J. Automot. Mech. Eng.

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“…Parlak, Islamoglu [35] used ANNs to predict specific fuel consumption and exhaust temperature for a diesel engine. Ghobadian, Rahimi [36]analysed the diesel engine performance and exhaust emission analysis using waste cooking biodiesel fuel with an ANN. Deh Kiani, Ghobadian [37] used ANN modelling to predict the engine brake power, output torque, and exhaust emissions of a spark ignition engine.…”

Section: Introductionmentioning

confidence: 99%

Effect of the Injection Timing on the Performance of a Diesel Engine Using Diesel-Biodiesel Blends

Rostami¹,

Ghobadian²,

Kiani³

2014

Int. J. Automot. Mech. Eng.

Self Cite

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In this study, the effect of fuel injection timing on the performance of a diesel engine was investigated experimentally and analytically using diesel-biodiesel blends. Different experiments were carried out on the diesel engine at engine speeds of 1200, 1600, 2000 and 2400 rpm. The injection timing was regulated for 10, 15 and 20 degree crank angle before top dead centre. The experimental results of engine torque, brakespecific fuel consumption (BSFC), cylinder pressure, and exhaust gas temperature for fuel blends of B20, B40, and B100 at different engine speeds and injection timings were recorded. The results showed that advancing the fuel injection timing for fuel blends of B20, B40, and B100 increased engine torque by approximately 2.1%, 2.9% and 6.3%, respectively, and decreased maximum BSFC by approximately 2.7%, 3.3% and 6.6%, respectively. Then, an artificial neural network (ANN) was used to predict engine performance. The injection timing, engine speed, and fuel blends were used as input parameters whereas engine performance parameters such as engine torque, BSFC, peak cylinder pressure, and exhaust gas temperature were used as the output parameters. The results showed that an ANN is a good tool to predict engine performance.

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“…Therefore, an ANN is utilized as a virtual model for the engine to provide the optimization process with an estimate of engine performance and emissions parameters. Related studies that have used ANN to predict engine performance and exhaust emissions include studying the performance and exhaust emissions of a diesel engine [23]; developing correlation among torque, brake power, BSFC, volumetric e ciency, and exhaust emissions [24]; and predicting the engine brake power, torque, and the exhaust emissions [25]. Other related works include those that have focused on the use of optimization methods in engine improvement [26][27][28].…”

Section: Motivation and Related Workmentioning

confidence: 99%

Performance and emissions optimization of an ethanol-gasoline fueled SI engine with oxygen enrichment using artificial bee colony algorithm

2017

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Abstract. The use of arti cial neural network in conjunction with arti cial bee colony algorithm is proposed as a method for performance and emissions optimization of an SI engine. The case study here involves the oxygen enriched combustion of an SI engine fueled with hydrous ethanol and gasoline. In this study, the engine was considered as a black box and its performance and emissions were extracted experimentally at di erent intake air oxygen concentrations, hydrous ethanol injection rates, and ethanol concentration in the hydrous ethanol mixture. Then, the simultaneous injection of hydrous ethanol and oxygen enriched combustion was investigated to maximize the fuel conversion e ciency and minimize the CO and NOx emissions. Therefore, an objective function consisting of both the emission and performance parameters was optimized using the Arti cial Bee Colony algorithm. The engine model used in this optimization process was obtained from an Arti cial Neural Network trained with experimental engine data. For operating speed of 3000 rpm, the optimization results indicated 1.21% improvement in fuel conversion e ciency and 31.11% and 13.94% reduction in CO and NOx emissions, respectively. At the speed of 2000 rpm, fuel conversion e ciency improved by 4.11% and CO emission decreased by 18.73%, while NOx concentration increased by 28.35%.

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Diesel engine performance and exhaust emission analysis using waste cooking biodiesel fuel with an artificial neural network

Cited by 451 publications

References 27 publications

Comparative study of diesel engine performance and emission with soybean and waste oil biodiesel fuels

Comparative study of diesel engine performance and emission with soybean and waste oil biodiesel fuels

Effect of the Injection Timing on the Performance of a Diesel Engine Using Diesel-Biodiesel Blends

Performance and emissions optimization of an ethanol-gasoline fueled SI engine with oxygen enrichment using artificial bee colony algorithm

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