E. Alizadeh Haghighi, S. Jafarmadar, H. Taghavifar,
Volume 3, Issue 4 (12-2013)
Abstract
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.
Sina Hassanzadeh Saraei, Shahram Khalilarya, Samad Jafarmadar, Saeed Takhtfirouzeh, Hadi Taghavifar,
Volume 8, Issue 4 (12-2018)
Abstract
Pollutant emissions from diesel engines are significantly affected by fuel injection strategies that could reduce NOx and Soot emissions. For the first time and in this study, numerical simulations were performed to consider the influences of changing the injection duration in each pulse of the double injection strategies on in-cylinder parameters and pollutant emissions. Results confirmed that double injection strategies could influence the in-cylinder temperature, which leads to a reduction in NOx and soot emissions. Additionally, it is seen that decreasing the injection duration could increase the in-cylinder peak pressure and temperature. It could also reduce the soot emission owing to the better fuel atomization. Moreover, RATE+0.5CA case, which injection duration for each pulse increases 0.5 CA, was selected to be the optimum case in reduction of pollutant emissions.
