Steady-State Analysis and Voltage Control of the Self-Excited Induction Generator Using Artificial Neural Network and an Active Filter

Zidani, Youssef; Zouggar, Smail; Elbacha, Abdelhadi

doi:10.1007/s40998-017-0046-0

Cited by 11 publications

(4 citation statements)

References 8 publications

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“…Ref. [33] proposed an ANN based system to control the voltage and frequency of a self-excited induction generator. An external excitation circuit containing a power-switched inductance or capacitor is used to compensate for the proposed system reagent demand.…”

Section: Ann Applications In Electrical Machinesmentioning

confidence: 99%

Artificial neural network analysis on an axial flux permanent magnet generator having variable air gap and power regime

Tekerek

Kurt

2021

Sādhanā

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In the present study, an artificial neural network (ANN) design has been proposed to analyze and estimate the output quantities of a newly manufactured generator, namely axial flux permanent magnet generator (AFPMG). The machine has been designed with a maximum power of 3 kW for the household electric power generation. As one of the innovative points, this machine has a variable air gap between the stator and the rotors, thereby the maximal power scale can be determined easily by adjusting the air gap between 2 mm and 7 mm. It means that the maximal power has values between 3 kW and 1.5 kW. ANN approach for such a machine is important in the sense that the estimation of output power, voltage and current values under various speeds and electrical loads are vital for the optimum operation of the machine. The designed ANN algorithm has been successful to estimate the output power and voltage of the newly produced generator for different air gap and speed and electrical load parameters.

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Section: Ann Applications In Electrical Machinesmentioning

confidence: 99%

Artificial neural network analysis on an axial flux permanent magnet generator having variable air gap and power regime

Tekerek

Kurt

2021

Sādhanā

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“…Also, NN controller could estimate the power values higher than that for the experimental limits, and it can be a suitable technique. Some modification and improvements proposed for the classical direct torque controller, e.g., Zemmit et al (2016) [75] designed an ANN-Direct Torque Control in which the IP and switching table have been replaced by a new artificial neural network. This strategy can reduce the high torque and flux ripples.…”

Section: Neural Computingmentioning

confidence: 99%

Review of Soft Computing Models in Design and Control of Rotating Electrical Machines

et al. 2019

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Rotating electrical machines are electromechanical energy converters with a fundamental impact on the production and conversion of energy. Novelty and advancement in the control and high-performance design of these machines are of interest in energy management. Soft computing methods are known as the essential tools that significantly improve the performance of rotating electrical machines in both aspects of control and design. From this perspective, a wide range of energy conversion systems such as generators, high-performance electric engines, and electric vehicles, are highly reliant on the advancement of soft computing techniques used in rotating electrical machines. This article presents the-state-of-the-art of soft computing techniques and their applications, which have greatly influenced the progression of this significant realm of energy. Through a novel taxonomy of systems and applications, the most critical advancements in the field are reviewed for providing an insight into the future of control and design of rotating electrical machines.

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“…Here, the electric excitation part of the structure is the salient pole type, and it needs to use the structure of a carbon brush slip ring, which will affect the service life of the generator. In terms of voltage control, on the basis of the traditional electronic control system, some improved voltage stabilizing control system with neural network control, robust control, and sliding mode control were proposed in [15][16][17], respectively, and achieved good voltage stabilizing performance.…”

Section: Introductionmentioning

confidence: 99%

Development of Brushless Claw Pole Electrical Excitation and Combined Permanent Magnet Hybrid Excitation Generator for Vehicles

Geng

Zhang

et al. 2020

Energies

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Aiming at the problems of large excitation loss and low power generation efficiency of silicon rectifier generators and the unstable output voltage of permanent magnet (PM) generators, a hybrid excitation generator (HEG) with suspended brushless claw pole electrical excitation rotor (EER) and combined magnetic pole PM rotor is proposed in the present work. With only one fractional slot winding stator, the generator adopts PM field as the main magnetic field and electrical excitation field as the auxiliary magnetic field, which not only retains the advantages of high efficiency of PM generators but also effectively reduces excitation consumption. The main structure parameters and the design method were analyzed, and a simulation analysis of no-load magnetic field distribution and flux regulation ability was carried out using finite element software to verify the rationality of the hybrid excitation parallel magnetic circuit design. Moreover, the no-load, load, regulation, and voltage regulation characteristics of the designed generator were tested, and the results show that the designed generator has a wide range of voltage regulation, which can ensure stable output voltage under variable speed and load conditions.

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Steady-State Analysis and Voltage Control of the Self-Excited Induction Generator Using Artificial Neural Network and an Active Filter

Cited by 11 publications

References 8 publications

Artificial neural network analysis on an axial flux permanent magnet generator having variable air gap and power regime

Artificial neural network analysis on an axial flux permanent magnet generator having variable air gap and power regime

Review of Soft Computing Models in Design and Control of Rotating Electrical Machines

Development of Brushless Claw Pole Electrical Excitation and Combined Permanent Magnet Hybrid Excitation Generator for Vehicles

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