Finite element analysis of switched reluctance motor with rotor position based control

Marcsa, Dániel; Kuczmann, Miklós

doi:10.1556/606.2016.11.3.14

Cited by 4 publications

(1 citation statement)

References 16 publications

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“…The following are improvements: The issue of whether poles are aligned [1] affects how the reluctance is calculated using a direct technique [19]. As an alternative, an approach that works well regardless of the position of the rotor is suggested in [20], [21]. An FE-assisted lookup methodology [22], [24] or a direct measurement method [25] are reported concerning magnetic saturation.…”

Section: Magnetic Equivalent Circuit (Mec)mentioning

confidence: 99%

Modelling methods and structure topology of the switched reluctance synchronous motor type machine: a review

Abdulah

Shukor

Othman

et al. 2023

IJPEDS

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The switched reluctance synchronous motors (SRSM) have been utilised as replacements for induction motors (IM) and permanent magnet synchronous motors (PMSM). The SRSM is a feasible solution for electric motors because of its robust and straightforward structure, resulting in low maintenance, manufacturing, and operating costs. However, the SRSM has several flaws, including low mean torque, low torque density and excessive torque ripples. The SRSM performance can be improved by considering the structure topology and driving system. This paper reviewed the performance characteristic of SRSM based on the structural topology. Several literature studies on the segmented structure topologies of SRSM were compared with the conventional structures. The performance of the SRSM can be estimated by using either numerical or analytical methods. The FEA and BEM are numerical techniques extensively used to optimise electrical motor performance. Although the numerical method can accurately estimate motor performance, the significant drawback is quite complicated, time-consuming, and difficult to implement the control algorithm with FEA software. However, the analytical method, especially the MEC method, is faster in evaluating motor performance and significantly reduces computational complexity, either with or without solving high-dimensional system matrices.

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