Intelligent Maximum Power Tracking Control For a Wind Energy System Based on Magnetic Gear Generator

Belkhir, K. S.

doi:10.48084/etasr.2851

Cited by 4 publications

(3 citation statements)

References 13 publications

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“…Angle ( 1 This technique has very interesting characteristics such as learning and self-organization. Neural networks can be thought of as black boxes [21][22]. The calculation of the mean values of the currents and the angles which separate them in the tridimensional space leads to the results presented in tabulated form in Figure 9.…”

Section: Tridimensional Methods For Fault Diagnosismentioning

confidence: 99%

New Approach in the Fault Tolerant Control of Three-Phase Inverter Fed Induction Motor

Boumous

2020

Eng. Technol. Appl. Sci. Res.

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This article provides an improved fault-tolerant control scheme for inverter-powered induction motors. The proposed strategy addresses the cancellation of power switch failures (IGBTs) regardless of their location in a reconfigurable induction motor control. The proposed fault-tolerant topology requires only minimal hardware modifications of the conventional six-switch three-phase drive, mitigating IGBT failures through reconfiguration based on the substitution of an entire inverter arm. The detection mechanism is based on the tridimensional method from which a database will be used for the learning of the neural network. In this method, the current from the stator is used as input to the system, so access to the induction motor is not necessary.

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Section: Tridimensional Methods For Fault Diagnosismentioning

confidence: 99%

New Approach in the Fault Tolerant Control of Three-Phase Inverter Fed Induction Motor

Boumous

2020

Eng. Technol. Appl. Sci. Res.

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“…Coaxial magnetic gears (CMGs) were first introduced two decades ago by Atallah et al [3], and since then there has been a growing interest in their use in different applications, including power generation [4,5] and aerospace [6]. The analytical solutions of the scalar magnetic potential of CMGs and the subsequent magnetic flux densities and induced torques in the two rotors were computed analytically by Tzouganakis et al [7].…”

Section: Introductionmentioning

confidence: 99%

Detailed Investigation of the Eddy Current and Core Losses in Coaxial Magnetic Gears through a Two-Dimensional Analytical Model

Nikolarea,

Tzouganakis,

Gakos

et al. 2024

MCA

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This work introduces a 2D model that calculates power losses in coaxial magnetic gears (CMGs). The eddy current losses of the magnets are computed analytically, whereas the core losses of the ferromagnetic segments are computed using an analytical–finite element hybrid model. The results were within 1.51% and 3.18% of those obtained from an FEA for the eddy current and core losses in the CMG for an indicative inner rotor speed of 2500 rpm. In addition, the significance of the circumferential magnet segmentation is demonstrated in the CMGs. Furthermore, a parametric investigation of the efficiency of the system for different applied external loads is carried out. Finally, a mesh sensitivity analysis is performed, along with the computation of the average power losses throughout one full period, resulting in an at least 80% reduction in computational costs with a negligible effect on accuracy. The developed model could be a valuable tool for the minimization of power losses in CMGs since it combines high accuracy with a low computational cost.

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“…System objects are usually individual devices: heat exchangers, extractors, compressors, etc. Nowadays, the use of artificial intelligence, expert systems, or neural networks is increasingly utilized to solve many technical and engineering problems [1]. Engineering practice requires a correct assessment of the mathematical model describing a given system by means of variables.…”

Section: Introductionmentioning

confidence: 99%

Application of the Dependency Graph Method in the Analysis of Automatic Transmission Gearboxes

Deptuła

2021

Eng. Technol. Appl. Sci. Res.

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The current article discusses the use of the dependency graph method to design and analyze automatic transmissions. Different goals may be served by modeling an automatic transmission using graphs. The most important of them are: determining the gear ratios for gears and the analysis of speed and acceleration of the rotating elements. Game tree-structure methods can be used to analyze the functional schemes of the selected gears. This paper describes the method of generating a system of kinematics equations for signal dependency graphs. This allows the generalization and extension of the algorithmic approach, and also further analyses and syntheses, such as checking the isomorphism of the proposed solutions and determining the validity of the structure and the operational parameters of the analyzed gears.

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Intelligent Maximum Power Tracking Control For a Wind Energy System Based on Magnetic Gear Generator

Cited by 4 publications

References 13 publications

New Approach in the Fault Tolerant Control of Three-Phase Inverter Fed Induction Motor

New Approach in the Fault Tolerant Control of Three-Phase Inverter Fed Induction Motor

Detailed Investigation of the Eddy Current and Core Losses in Coaxial Magnetic Gears through a Two-Dimensional Analytical Model

Application of the Dependency Graph Method in the Analysis of Automatic Transmission Gearboxes

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