Study and the effects of ignition timing on gasoline engine performance and emissions

Zareei, Javad; Kakaee, Amir-Hasan

doi:10.1007/s12544-013-0099-8

Cited by 50 publications

(21 citation statements)

References 5 publications

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“…As shown in the plot, for all hydrogen addition levels, the HC emissions are reduced as the spark timing is gradually retarded. The shorter quenching distance, high flame speed, and low ignition energy of the hydrogen reduces the combustion duration and in turn decreases the probability of occurrence of slow‐burning and incomplete combustion cycles 17. Thus the HC emissions from the hydrogen‐enriched engine operation are obviously lower than those from the original at a specified spark advance; this was due to increased hydrogen volume fraction and high flame speed of hydrogen.…”

Section: Resultsmentioning

confidence: 99%

Experimental Investigation of Variations in Spark Timing using a Spark‐Ignition Engine with Hydrogen‐Blended Gasoline

Shivaprasad¹,

Chitragar

Kumar

2015

Energy Tech

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This study describes an experiment conducted using an electronically controllable single‐cylinder high‐speed gasoline engine to analyze the performance and emissions characteristics of various hydrogen–gasoline blends. The experiments have been conducted for various engine speeds and spark timings at the wide open throttle position. The experimental results revealed that the engine brake thermal efficiency and brake mean effective pressure first increase and then decrease with the increase engine speed at all spark timings. The minimum amount of brake specific energy consumption was observed for 20 % hydrogen addition in the total fuel blend at 3000 rpm engine speed and 14 °crank angle (CA) before top dead center (BTDC) spark timing. Hydrocarbon and carbon monoxide emissions were reduced with the retardation of spark timings. Nitrogen oxide emissions were continuously increased with the addition of hydrogen in the fuel blend as well as spark timing advance.

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Section: Resultsmentioning

confidence: 99%

Experimental Investigation of Variations in Spark Timing using a Spark‐Ignition Engine with Hydrogen‐Blended Gasoline

Shivaprasad¹,

Chitragar

Kumar

2015

Energy Tech

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“…The ideal gas model expresses the relationship between the mass   g m  in the control volume, its volume   g V  , its pressure   g p  , and its temperature   g T  , [14], [15]:…”

Section: Ideal Gas Modelmentioning

confidence: 99%

“…However, the geometry of each zone must be followed in order to calculate the heat transfer and the composition of the burned and unburned gases. The two-zone model is used to predict concentrations of combustion products at any engine operating conditions [5], [6]. In this paper, engine simulation is based on a single-zone thermodynamic model developed to characterize each of the engine cycle phases in order to predict the relevant engine performance.…”

Section: Introductionmentioning

confidence: 99%

Analytical and Experimental Study of a Naturally Aspirated Indirect Injection 4-Stroke Spark Ignition Engine

Slimane

Menacer²,

Bouchetara

2019

mech

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One of the objectives of this study is to elaborate an engine cycle simulation program in FORTRAN language to analyze the influence of operating parameters on the performance (theeffective power, torque and specific fuel consumption) of a four-stroke gasoline engine (Ford ZSG 416 gasoline engine) for different engine operating parameters. The GT-Powerengine simulation software was used to compare the results obtained with the developed computer program and to improve it. In this program, a single-zone thermodynamicmodel was considered, which describes each phase of the engine cycle. In order to validate the developed program, a comparison of the experimental results with those obtainedusing GT-Power software was carried out. The other objective of this paper is to investigate the influence of a number of significant engine parameters such as compression ratio, cylinder wall temperature, cylinder diameter, stroke-bore ratio and ignition angle on the performance of the chosen engine. Examining the experimental results and those obtained with the developed program, it was observed that the power difference was in the order of ± 3%, the torque difference was ± 6%, while the BSFC difference was about ± 10%. It has been noted that the most significant parameters in improving the performance of the gasoline engine are the compression ratio, the fuel/air ratio, the engine geometry and the ignition begin. The variation of these parameters was not arbitrary, the knock criteria, in other words, the achievement of normal combustion were taken into account.

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“…To achieve maximum power can only be achieved if the ratio of air and fuel right and also with the right time too. Modify the ignition timing by advancing the ignition timing to obtain a more optimal performance (Zareei and Kakaee, 2013). This is done because there is a time lag between the arcing sparks with the onset of combustion of fuel and also depends on the nature of combustion properties of each fuel has a specific time to end the combustion process.…”

Section: Injection System (Fi)mentioning

confidence: 99%

Optimization and Prediction of Motorcycle Injection System Performance with Feed-Forward Back-Propagation Method Artificial Neural Network (ANN)

Syahrullah¹,

Sinaga²

2016

American Journal of Engineering and Applied Sciences

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This research studied the use of Artificial Neural Network (ANN) using feed-forward back-propagation model to optimize and predict the performance of a motorcycle fuel injection systems of gasoline. The parameters such as speed, throttle position, ignition timing and injection timing is used as the input parameters. While the parameters of fuel consumption and engine torque is used as the output layer. LavenbergMarquardt model type with train function tanh sigmoid and 25 neurons number is used to generate the target value and the desired output. Variation of ignition timing as optimization variable in a wide range of speed and throttle position is used in experimental tests. ANN is used to investigate the prediction of performance motorcycle engines and compared with the test results. Results showed that the operation of ANN in predicting engine performance is very good. From the test results obtained a smooth contour MAP compared to the initial state. The prediction result and performance test show a good correlation in small error value of training and test that is regression with range 0.98-0.99, mean relative error with range 0.1315-0.4281% and the root mean square error with range 0.2422-0.9754%. This study shows that the feed-forward back propagation on ANN model can be used to predict accurately the performance of a motorcycle engine injection system.

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Study and the effects of ignition timing on gasoline engine performance and emissions

Cited by 50 publications

References 5 publications

Experimental Investigation of Variations in Spark Timing using a Spark‐Ignition Engine with Hydrogen‐Blended Gasoline

Experimental Investigation of Variations in Spark Timing using a Spark‐Ignition Engine with Hydrogen‐Blended Gasoline

Analytical and Experimental Study of a Naturally Aspirated Indirect Injection 4-Stroke Spark Ignition Engine

Optimization and Prediction of Motorcycle Injection System Performance with Feed-Forward Back-Propagation Method Artificial Neural Network (ANN)

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