Cogging torque sensitivity considering imperfect magnet positioning for permanent magnet machines of different slot and pole count

Bramerdorfer, Gerd; Marth, Edmund; Goldbeck, Gereon

doi:10.30941/cestems.2020.00030

Cited by 10 publications

(2 citation statements)

References 37 publications

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“…The profile of the cogging torque is highly sensitive to the length, size and position of the magnets as extensively documented in the literature. Examples include [5], [20], [21], and [22]. Since the cogging torque is generated due to the interaction of the rotor MMF harmonics with the air-gap permeance function any minor change in these parameters (i.e.…”

Section: B Modulated Magnetic Flux Density Calculationmentioning

confidence: 99%

Deep Learning Based Design Methodology for Electric Machines: Data Acquisition, Training and Optimization

Poudel

Amiri

2023

IEEE Access

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This paper presents an automated deep learning-based design methodology to facilitate the design and optimization processes in electro-mechanical energy conversion devices. To validate the generality of the model, a complex machine structure with hybrid Permanent Magnets (PMs) is selected as the case study. First, the machine's geometrical topology and the respective design variables are described in the cylindrical coordinate system and programmed into a Finite Element (FE) software package. Next, the program sweeps through the predefined ranges of selected design variables and captures corresponding air-gap flux distribution through an automated FE-based parametric analysis. The air-gap flux density data is post-processed and fed into a deep neural network (DNN) training algorithm. In particular, 10,000 data sets are utilized for training the DNN model. The trained model successfully predicts the machine's performance for any random set of parameters, as confirmed via FE. Finally, by leveraging the trained model, the structural parameters of the machine are optimized to limit higher-order spatial flux harmonics and the cogging torque. INDEX TERMSData acquisition, deep learning, finite element, permanent magnet machine. BIKRANT POUDEL (Graduate Student Member, IEEE) received the B.S. degree in electronics and communication engineering from Tribhuvan University, Kathmandu, Nepal, in 2013, and the M.S. degree in electrical engineering and the Ph.D.

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Section: B Modulated Magnetic Flux Density Calculationmentioning

confidence: 99%

Deep Learning Based Design Methodology for Electric Machines: Data Acquisition, Training and Optimization

Poudel

Amiri

2023

IEEE Access

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“…Assembly tolerance can be related to the stator and rotor. On the rotor side, the magnets can be displaced in circumferential or even axial direction [13]. Moreover, rotor eccentricity in the form of static, dynamic, or mixed also can occur, which depends on the bearing placement tolerances [14].…”

Section: Introductionmentioning

confidence: 99%

Manufacturing-Induced Cogging Torque in Segmented Stator Permanent-Magnet Machines With Respect to Steel Punching

et al. 2022

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There are applications like electric power-assisted steering system in which strict requirements on the cogging torque of the machine should be fulfilled. Numerous techniques and methods are introduced in order to minimize the inherent cogging torque of the machine, but manufacturing tolerances and imperfections still can cause extra cogging torque. In this paper, the impact of punching on the manufacturing-induced cogging torque of segmented permanent-magnet synchronous machines is investigated. The punching model is implemented by modifying the BH curve of the steel as a function of distance from the cut edges. The parameters of the new BH curve are identified by means of standard Epstein frame measurements using steel strips with different widths. Then, the punching model is incorporated into the finite element model of a 10-pole 12-tooth segmented stator machine designed for power steering application. It is observed that deviation among the magnetic properties of the teeth caused by punching can introduce extra low-order harmonics in the cogging torque of the machine. The amplitude of the new orders can be comparable or even much bigger than the inherent orders, where not only the magnitude of deviation but also the arrangement of teeth with given punching parameters play a role.

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A novel African buffalo optimization for the minimization of cogging torque in modified permanent magnet DC motor

Khan

Bhattacharyya

Singh³

2021

Sustainable Energy Technologies and Assessments

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Cogging torque sensitivity considering imperfect magnet positioning for permanent magnet machines of different slot and pole count

Cited by 10 publications

References 37 publications

Deep Learning Based Design Methodology for Electric Machines: Data Acquisition, Training and Optimization

Deep Learning Based Design Methodology for Electric Machines: Data Acquisition, Training and Optimization

Manufacturing-Induced Cogging Torque in Segmented Stator Permanent-Magnet Machines With Respect to Steel Punching

A novel African buffalo optimization for the minimization of cogging torque in modified permanent magnet DC motor

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