2-D analytical subdomain model for high-speed permanent-magnet machines

Gilson, Adrien; Tavernier, Stephan; Dubas, Frédéric; Depernet, Daniel; Espanet, Christophe

doi:10.1109/icems.2015.7385280

Cited by 14 publications

(11 citation statements)

References 9 publications

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“…The open-circuit and on-load parameters can also be included [11,12]. The magnetic field distribution, phase back-emf, electromagnetic torque, and winding inductance are then predicted in this model [10][11][12][13][14]. The common formulae for analytical sub-domain model using magnetic vector potential in the permanent magnet (A z1 ), air-gap (A z2 ), winding slots (A z3i ), and slotopenings (A z4i ) in 2-D polar coordinates are described in (1) to (4) [15].…”

Section: Analytical Sub-domain Modellingmentioning

confidence: 99%

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Optimization of surface-mounted permanent magnet brushless AC motor using analytical model and differential evolution algorithm

Mohamed

Ishak

2019

Journal of Electrical Engineering

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This paper discusses the optimization of surface-mounted permanent magnet brushless AC (PMBLAC) motor using Analytical Sub-domain model with Differential Evolution Algorithm (ASDEA). Only two regions were considered in this analytical sub-domain model, ie magnet and airgap regions, with assistance of Complex Relative Permeance Function (CRPF) to account for the stator slotting effect. Five machine parameters were chosen to be optimized, namely the magnet arc-pole-pitch ratio, slot opening width, magnet thickness, airgap length and stator inner radius. The optimization process has four objectives, ie minimum torque ripple, low cogging torque, high efficiency, and high output torque. The results from the optimized ASDEA were compared with the Analytical Sub-domain Genetic Algorithm (ASGA) and further validated against 2-D finite element model (FEM). Results show a good agreement between analytically optimized models and finite element model. The ASDEA has faster computational time compared to ASGA, and this provides benefit in terms of reducing the machine design parameterization time and less redundancy work required to achieve motor design specifications.

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Section: Analytical Sub-domain Modellingmentioning

confidence: 99%

“…The i -th vector of the population at the current generation can be represented as shown in (12). Each parameter has minimum and maximum bounds as shown in (13) and (14), respectively [33,34].…”

Section: Differential Evolution Optimizationmentioning

confidence: 99%

Optimization of surface-mounted permanent magnet brushless AC motor using analytical model and differential evolution algorithm

Mohamed

Ishak

2019

Journal of Electrical Engineering

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“…2) Comparison with FEM: An efficient implementation of SDMs can lead to much lower computation time than FEM, as presented in [58]. Tab.…”

Section: Comparison On Computing Performance Of Sdmsmentioning

confidence: 99%

A review of subdomain modeling techniques in electrical machines: Performances and applications

Devillers

Besnerais²,

Lubin

et al. 2016

2016 XXII International Conference on Electrical Machines (ICEM)

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This paper reviews the recent developments of semi-analytical subdomains modeling techniques to compute the flux density distribution in electrical machines by the exact solving of Maxwell equations. It is shown that with an appropriate development methodology and numerical implementation, these harmonic models break the traditional compromise between accuracy and computation time that must be done using finite element or other analytical methods. Besides that, subdomains model development techniques have been improved to overcome its topological limitations This fact is demonstrated on three different subdomains models in comparison with finite element methods in terms of accuracy and processing time. The first one is a subdomains model of a surface permanent-magnet synchronous machine, the second one is for an inset permanentmagnet synchronous machine, and the third one is for a squirrelcage induction machine. Thanks to an efficient implementation method, a very low computation time is obtained. The robustness of the subdomains on the geometrical assumptions is also demonstrated.

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“…Conduction losses of the diodes result from the current and the voltage drop across. Those losses are computed with equation (6).…”

Section: Mosfet Commutation Lossesmentioning

confidence: 99%

“…In that category, subdomain models are particularly accurate [3,4] since they can take into account the slotting effect and the eddy current reaction field [5]. In this paper, a 2-D analytical subdomain model such as the one described in [6] is used to evaluate the electromagnetic field in the machine.…”

Section: A Analytical Modelmentioning

confidence: 99%

Coupled Electronic and Magnetic Fast Simulation for High-Speed Permanent-Magnet Drive Design

Gerber

Gilson

Depernet

et al. 2016

2016 IEEE Vehicle Power and Propulsion Conference (VPPC)

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The interest in high speed electrical machines for automotive applications has increased recently. This includes electrically-assisted turbochargers (EAT), air compressors for fuel-cells and waste heat recovery (WHR) generators. For these kinds of application working in elevated temperature environments, the losses in the machine and in the power electronics should be carefully analyzed. In this context, this paper presents a coupled electronic and magnetic simulation and its application on a high-power high-speed motor. The coupling between the two models is mainly linked to the phase currents and their impact on the electronic driver. In addition, motor performances must be considered to optimize the overall system efficiency. However, optimizations of electronic driver and electric motor are very time-consuming since they are based on finite element methods for magnetic simulations and on Kirchhoff equations resolution for electronic simulations. Therefore, this paper presents a fast coupled model to increase the computation speed and its application to optimize a system using a high-power high-speed motor with special focuses on motor rotor losses and overall efficiency.

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2-D analytical subdomain model for high-speed permanent-magnet machines

Cited by 14 publications

References 9 publications

Optimization of surface-mounted permanent magnet brushless AC motor using analytical model and differential evolution algorithm

Optimization of surface-mounted permanent magnet brushless AC motor using analytical model and differential evolution algorithm

A review of subdomain modeling techniques in electrical machines: Performances and applications

Coupled Electronic and Magnetic Fast Simulation for High-Speed Permanent-Magnet Drive Design

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