matlab simulink

Aim of this paper is to attain the highest voltage sag and swell compensation using a direct converter-based DVR topology. The projected DVR topology consists of a direct converter with bidirectional switches, a multi winding transformer with three primary windings and secondary winding and a series transformer. When voltage swell occurs in a phase, the same phase voltage can be utilized to mitigate the swell as huge voltage exists in the phase where swell has occurred. So it is possible to mitigate an infinite amount of swell. In all the DVR topologies, the converter is only used to synthesize the compensating voltage. The range of voltage sag mitigation depends upon the magnitude of input voltage available for the converter. If this input voltage of the direct converter is increased, then the range of voltage compensation could also be increased. Input voltage of the direct converter is increased using the multi winding transformer. The direct converter is synthesizing the compensating voltage. This compensating voltage is injected in series with the supply voltage through the series transformer and the sag is mitigated. In this proposed topology, the input voltage for the direct converter is increased by adding the three phase voltages using a multi winding transformer. Thus the voltage sag compensating range of this topology is increased to 68% and the swell compensating range is 500%. Ordinary PWM technique has been used to synthesize the PWM pulses for the direct converter and the THD of the compensated load voltage is less than 5%. This topology is simulated using MATLAB Simulink and the results are shown for authentication.

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.

In this article determination of appropriate valve timing using sensitivity analysis problem is investigated for a gasoline four stroke engine. In the first part of this study a 4-storke Spark Ignition engine (XU7JP4/L3) including its different systems such as inlet and exhaust manifold, exhaust pipe and engine geometry are modeled using GT-Power software and the model is coupled with MATLAB/Simulink to be able to control input and output parameters. Then in order to find the best model that fits experimental data, sensitivity analysis is performed and the best unknown parameters that can best model the engine are obtained. The input parameters are considered to be the inlet port temperature and pressure, and manifold friction coefficient. The target was achieving the least square error in engine power, torque and fuel consumption. In the second part of the study the optimized model is used for the sensitivity analysis and minimizing the engine specific fuel consumption up to 10 percent reduction in specific fuel consumption as a target. Sensitivity analysis is used for finding the best valve timing in different engine speeds to achieve the target.