Search published articles

Showing 3 results for Gt-Power

A. Kakaee, M. Keshavarz,
Volume 2, Issue 3 (7-2012)

In this study it has been tried, to compare results and convergence rate of sensitivity analysis and conjugate gradient algorithms to reduce fuel consumption and increasing engine performance by optimizing the timing of opening and closing valves in XU7/L3 engine. In this study, considering the strength and accuracy of simulation GT-POWER software in researches on the internal combustion engine, this software has been used. In this paper initially all components of engine have been modeled in GT-POWER. Then considering the experimental result, results confirmed the accuracy of the model. After model verification, GT-POWER model with MATLAB-SIMULINK are coupled each other, to control the inputs and the outputs by sensitivity analysis and conjugate gradient algorithms. Then the results compared with experimental results of initial engine too. The results indicated that optimal valve timing significantly reduced brake specific fuel consumption and when is used variable valve system for opening and closing angle of intake and exhaust valves, the mean improvement percentage in brake specific fuel consumption from sensitivity analysis is nearly 5.87 and from conjugate gradient is about 6.69. too, for example with increasing engine speed late closing intake valve causes optimized brake specific fuel consumption and from 3500rpm this trend stops and in 4000rpm and 4500rpm early closing of intake valve results in more optimized brake specific fuel consumption. Then up to 6000rpm again late closing of valve would be favorable. Also results indicated that convergence rate of conjugate gradient algorithm to reaching the optimal point is more than sensitivity analysis algorithm.

A.h Kakaee, Sh. Mafi,
Volume 7, Issue 3 (9-2017)

In this paper we aim to develop a predictive combustion model for a turbocharged engine in GT-Power software to better simulate engine characteristics and study its behavior under variety of conditions. Experimental data from combustion was initially being used for modelling combustion in software and these data were used for model calibration and result validation. EF7-TC engine was chosen for this research which is the first turbocharged engine designed and developed by IKCO and IPCO in Iran. After analyzing necessary theories for predictive combustion model and required steps for calibration of CombSITurb model in software, one final set of multipliers were calculated based on different sets derived for each engine speed and engine operation was simulated with this combustion model. In addition to improved predictability of engine model, comparing results of predictive model with non-predictive model shows better accuracy especially at lower engine speeds and less tolerance of results for each engine speed.
Javad Zareei, Saeed Ahmadi,
Volume 10, Issue 3 (9-2020)

In internal combustion engines, the turbocharger and alternative fuels are two important factors affecting engine performance and exhaust emission. In this investigation, a one-dimensional computational fluid dynamics with GT-Power software was used to simulate a six-cylinder turbocharged diesel engine and the naturally aspirated diesel engine to study the performance and exhaust emissions with alternative fuels. The base fuel (diesel), methanol, ethanol, the blend of diesel and ethanol, biodiesel and decane was used. The results showed that decane fuel in the turbocharged engine has more brake power and torque (about 3.86%) compared to the base fuel. Also, the results showed that the turbocharger reduces carbon monoxide and hydrocarbon emissions, and biodiesel fuel has the least amount of carbon monoxide and hydrocarbon among other fuels. At the same time, the lowest NOX emission was obtained by decane fuel. As a final result can be demonstrated that the decane fuel in the turbocharged engine and the biodiesel fuel in the naturally aspirated engine could be a good alternative ratio to diesel fuel in diesel engines.

Page 1 from 1     

© 2022 All Rights Reserved | Automotive Science and Engineering

Designed & Developed by : Yektaweb