Two Simple Analytical Models, Direct and Inverse, for Switched Reluctance Motors

Someşan, Liviu; Padurariu, Emil; Viorel, Ioan-Adrian

doi:10.2528/pierm12103001

Cited by 7 publications

(5 citation statements)

References 27 publications

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“…The SRM performance is heavily dependent on its design and control, which allows for minimized torque ripple and improved torque characteristics [16]. Over the years, few authors have discussed the problem of SRM performance sensitivity in relation to its dimensions.…”

Section: Introductionmentioning

confidence: 99%

RETRACTED: Geometric Parameter Optimization of Switched Reluctance Machines for Renewable Energy Applications using Finite Element Analysis

Mahmoud,

Khedher

2024

Period. Polytech. Elec. Eng. Comp. Sci.

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The choice of SRM design depends on the specific application and performance requirements. Factors such as power output, torque characteristics, and efficiency will all influence the choice of SRM design. To find an optimal geometry, it is therefore necessary to determine the effect of each parameter such as rotor pole angle, stator pole angle, stator external diameter, rotor diameter, air gap length, rotor yoke, stator yoke and shaft diameter on the machine performance. For this reason, this paper discusses a comparative study of the geometric parameters influence on SRM performance. The analysis is performed by finite element simulations based on the variation of rotor inclination, air gap length, stator and rotor polar arc variations of three machine topologies such as the three-phase 12/8 SRM, three-phase 6/4 SRM and four-phase 8/6 SRM. For a reliable comparison, these machines must have the same basic dimensions (stator outer diameter, rotor outer diameter and length) and operate in the same magnetic circuit saturation. Graphical and numerical results of torque and magnetic flux for three SRM topologies are highlighted. The presented study aims to provide reliable results on the dimensions to be adjusted for various applications.

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Section: Introductionmentioning

confidence: 99%

RETRACTED: Geometric Parameter Optimization of Switched Reluctance Machines for Renewable Energy Applications using Finite Element Analysis

Mahmoud,

Khedher

2024

Period. Polytech. Elec. Eng. Comp. Sci.

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“…The performance of the SRM depends heavily on its design and control, which allows reduced ripple in torque and improved torque-speed characteristics (Somesan et al, 2013). Few researchers have addressed the problem of the sensitivity of SRM performance in relation to its dimensions.…”

Section: Switched Reluctance Machine Model Considerationsmentioning

confidence: 99%

Moore-Penrose pseudo-inverse and artificial neural network modeling in performance prediction of switched reluctance machine

Mamede

Camacho

Araújo

et al. 2020

COMPEL

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Purpose The purpose of this paper is to present the Moore-Penrose pseudoinverse (PI) modeling and compare with artificial neural network (ANN) modeling for switched reluctance machine (SRM) performance. Design/methodology/approach In a design of an SRM, there are a number of parameters that are chosen empirically inside a certain interval, therefore, to find an optimal geometry it is necessary to define a good model for SRM. The proposed modeling uses the Moore-Penrose PI for the resolution of linear systems and finite element simulation data. To attest to the quality of PI modeling, a model using ANN is established and the two models are compared with the values determined by simulations of finite elements. Findings The proposed PI model showed better accuracy, generalization capacity and lower computational cost than the ANN model. Originality/value The proposed approach can be applied to any problem as long as experimental/computational results can be obtained and will deliver the best approximation model to the available data set.

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“…Most of these drawbacks can be mitigated by the development of control methods and/or geometry changes in its magnetic circuits. Accurate calculations of radial force and design of improved motor structures are the main routes for reducing SRM vibration (Somesan et al 2013). As far as the novelty is concerned, the main objective is to clarify the impact of the skewing methods in the SRM.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Skewing Effects on Radial Force for Different Topologies of Switched Reluctance Machines: 6/4 SRM, 8/6 SRM, and 12/8 SRM

Touati¹,

Araújo²,

Mahmoud³

et al. 2023

UPjeng

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Reducing vibration and noise in electrical machines for a given application is not an easy task, especially when the application imposes some restrictions. There are many techniques for reducing vibration based on design or on control. Switched reluctance motors (SRMs) have a double-saliency structure, which results in a radial pulsation force. Consequently, they cause vibration and acoustic noise. This paper investigates the correlation between the radial force and the skew angle of the stator and/or rotor circuits. The analysis is computed from two-dimensional (2D) transient magnetic finite-element analysis (FEA) of three machine topologies, namely the 12/8 three-phase SRM, the 6/4 three-phase SRM and the 8/6 four-phase SRM. Compared to SRM, these topologies have the same basic dimensions (stator outer diameter, rotor outer diameter, and length) and operate in the same magnetic circuit saturation. The flux linkage and torque characteristics of the different motors are presented. The radial force distributed on the stator yoke under various skewing angles is studied extensively by FEA for the three machines. It is also demonstrated the effect of skewing angles in the reduction of radial force without any reduction in torque production.

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Two Simple Analytical Models, Direct and Inverse, for Switched Reluctance Motors

Cited by 7 publications

References 27 publications

RETRACTED: Geometric Parameter Optimization of Switched Reluctance Machines for Renewable Energy Applications using Finite Element Analysis

RETRACTED: Geometric Parameter Optimization of Switched Reluctance Machines for Renewable Energy Applications using Finite Element Analysis

Moore-Penrose pseudo-inverse and artificial neural network modeling in performance prediction of switched reluctance machine

Analysis of Skewing Effects on Radial Force for Different Topologies of Switched Reluctance Machines: 6/4 SRM, 8/6 SRM, and 12/8 SRM

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