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Showing 2 results for Emission.

E. Alizadeh Haghighi, S. Jafarmadar, H. Taghavifar,
Volume 3, Issue 4 (12-2013)

Artificial neural network was considered in previous studies for prediction of engine performance and emissions. ICA methodology was inspired in order to optimize the weights of multilayer perceptron (MLP) of artificial neural network so that closer estimation of output results can be achieved. Current paper aimed at prediction of engine power, soot, NOx, CO2, O2, and temperature with the aid of feed forward ANN optimized by imperialist competitive algorithm. Excess air percent, engine revolution, torque, and fuel mass were taken into account as elements of input layer in initial neural network. According to obtained results, the ANN-ICA hybrid approach was well-disposed in prediction of results. NOx revealed the best prediction performance with the least amount of MSE and the highest correlation coefficient(R) of 0.9902. Experiments were carried out at 13 mode for four cases, each comprised of amount of plastic waste (0, 2.5, 5, 7.5g) dissolved in base fuel as 95% diesel and 5% biodiesel. ANN-ICA method has proved to be selfsufficient, reliable and accurate medium of engine characteristics prediction optimization in terms of both engine efficiency and emission.
Dr Ali Keshavarz, Fereshteh Khodamrezaee, Dr Sadegh Seddighi, Sepide Sarmast,
Volume 10, Issue 4 (12-2020)

This work investigates the effects of hydrogen addition to compressed natural gas (CNG) on combustion characteristics and emission reduction using a closed cycle simulation with exact geometry of piston and cylinder head. The effect of equivalence ratio on combustion characteristic were investigated using a spark ignition (SI) engine fueled with CNG and addition of 10% vol, 15% vol and 20%vol hydrogen. Two different speed of 1500 and 3000 rpm have considered at full load condition. The modeling includes ECFM combustion model combined with K-ζ-f turbulent modeland has been done by AVL Fire software. Different volume fraction of Hydrogen with different excess air modeled and validated with experimental data. The validation procedure included in-cylinder pressure profile, maximum pressure, angle of maximum pressure, indicated mean effective pressure, and carbon monoxide (CO) emission showing a good agreement with the experimental results. The value of the peak pressure increases by hydrogen addition and it takes place sooner as the hydrogen volume fraction increases. However, the mean effective pressure drops 3.5%, 7% and 15% for HCNG 10, HCNG15 and HCNG20, respectively. CO emission decreases by increasing the hydrogen volume fraction. The results also indicate that hydrogen addition in lean combustion causes more CO reduction compared to the fuel-rich mixtures.

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