Journal of Majlesi Journal of Mechatronic Systems
Volume:7 Issue: 4, Dec 2018

This paper suggests an Artificial Neural Network model (ANN) in order to increase propulsion capability and reduce fuel consumption in hybrid electric vehicles. All stages are implemented by Simulink of MATLAB software. The simulation is based on basic parameters of internal-combustion engine. The achieved results reveal the ability of suggested method to reduce fuel consumption and increase the lifetime of the vehicle components, including the battery due to reduction of travel disturbances and soft moving of the vehicle at different speeds. It is also possible to optimize the problem for various vehicles and all types of roads by changing the motion parameters and conditions of artificial Neural Network Parameterization.

Due to high energy demands around the world, there is a need to attend for searching an alternative renewable and sustainable energy source. Plant microbial fuel cell (PMFC) is the most promising technology to generate a renewable source of energy. In this paper, a PMFC system has been developed and the generation of electricity has been tested for 365 days. The PMFC generates a maximum voltage of 0.982 V which is not enough to power the electronic device. So a self-sustainable DC-DC boost converter presents and studies the performance of the boost converter with/without the super capacitor. The DC-DC boost converter boosts up the voltage from 0.982 V to 2.562 V of outputs. It was found that the energy harvester DC-DC boost converter with the super capacitor can deliver up to 2.562 V for 13 minutes which is sufficient to power sensor devices, communication and other remote broadcasts etc.

In this work, the vector control methods of doubly-fed induction generator (DFIG) in wind energy conversion systems are studied. In the methods under study, the proper voltage space vector of the rotor side converter is selected using a proportional-integral (PI) controllers. The artificial neural networks (ANNs) based on space vector modulation (SVM) which is used to control the inverter in order to reduce the reactive and active power ripples and minimize the total harmonic distortion (THD) of the rotor current. Various simulations are performed in Matlab/Simulink software on a DFIG system in order to investigate the dynamic performance and robustness of the proposed control methods against machine internal parameters variations.

Generally, the switch mode power supply input voltage source is constant or shows insignificant little varieties.in any case, when fuel call used input source the last assumption is not valid. A fuel cell stack is give a details of low and not controlled DC output voltage, moreover, when the demanded current increases the output voltage becomes low in a nonlinear form; from now on, suitable controller is required to taken the previously mentioned issues. In this article, a normal current-mode controller is planned to using a joined model for an energy unit stack and a boost converter; besides, the resolving control method increasing the system stability and output voltage regulation. The proposed energy system utilizes an energy component power (polymer electrolyte film fuel cell) and a boost converter passing on power of 900 W. the proposed controller execution for output voltage regulation by means of closed loop gain estimations and step load changes. What's more, a correlation amongst open-and closed- loop estimations is made, where the controller robustness is tried for vast load varieties and fuel cell stack output voltage changes are shows on simulation results.

Due to the dramatic growth in the electric power industry and the large gap between small and large loads and loads economic crisis that has gripped most of the world, an issue critical to the operation of power plants has become. Also growing use of traditional sources of energy and lack of response to this need has created a lot of problems around the world. Including that they can reduce fossil fuel resources, and the environmental impact of greenhouse gas increases noted. This problem has led to concerns of environmentally friendly technologies such as electric cars get more attention. Considering to the capability of bi-directional exchange power in vehicles, electric vehicles are a significant number of network connections To coordinated the management and intelligent control of an entity causing the network to be connected together, Considering In this type of electric vehicles as well as hardware that is installed in the parking lot, as they can quickly set up a small virtual power plant set-up costs are too high and behave. The main focus of this thesis is to develop a model in order to exploit the electrical grid in the smart grid the intelligent power network operation in the presence of electric vehicles can be connected to the network has been studied. This paper presents an optimal load management strategy for residential consumers that utilizes the communication infrastructure of the future smart grid. The strategy considers predictions of electricity prices, energy demand, renewable power production, and power-purchase of energy of the consumer in determining the optimal relationship between hourly electricity prices and the use of different household appliances and electric vehicles in a typical smart house. The proposed strategy is illustrated using two study cases corresponding to a house located in Zaragoza (Spain) for a typical day in summer. Results show that the proposed model allows users to control their diary energy consumption and adapt their electricity bills to their actual economic situation.

Power transformers play an important role in the transmission and distribution of electrical energy. Power transformers increase or decrease the voltage level without changing the power and frequency of alternating current (AC) electricity. Power transformers are divided into oil type and dry type transformers. Both two types have disadvantages of high cost and isolation problems etc. These problems are reduced by the optimization of transformer design parameters. In this study, the most optimal design dimension is determined by using the firefly algorithm, which is a new heuristic approach in calculating the volume of oil type power transformers at least time. At the same time, the performance comparison is made with the most preferred genetic algorithm, which is one of the other intuitive methods, and the advantages of the firefly algorithm are revealed. This work will provide both cost and time benefits for transformer manufacturers.

In this study, wavelet transform is applied for three phase to ground fault detection and classification which occur at different locations in a 765 kV, 50 Hz twelve phase transmission line. The information of distorted energy, approximate and high frequency detail coefficients included in a fault current signal is captured using wavelet transform. Faulted phase determination is also carried out using the proposed technique concurrently. The effectiveness of the proposed protection technique is validated for three phase to ground faults, and various values of fault type, fault inception time, fault resistance, and fault location. Test results show that the proposed technique effectively detects the three phase to ground fault and discriminates the faulty phase effectively.