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Article
Publication date: 24 June 2024

Yuki Hidaka

The purpose of this paper is to develop a novel optimization method that can improve the convergence of the multi-material topology.

Abstract

Purpose

The purpose of this paper is to develop a novel optimization method that can improve the convergence of the multi-material topology.

Design/methodology/approach

In the proposed method, the optimization procedure is divided into two steps. In the first step, a global search is performed to probabilistically determine the material distribution of multi-segmented magnets. In the second step, the design area is limited and a local search is performed to determine the detailed magnet shape.

Findings

Because the first optimization step determines the arrangement of the magnetization vectors according to the rotational position, as in a d-axis flux concentration orientation, the optimal solution can be obtained with a smaller volume of magnets than the conventional method.

Research limitations/implications

Because a few case studies are considered in this paper, additional verification is required, such as application to different types of motors, to clarify scalability.

Practical implications

The solution obtained using the proposed method has a smaller amount of magnet than the solution obtained using the conventional method and can fully satisfy the average torque constraint.

Originality/value

The proposed method differs from the conventional method in that the material distribution is determined according to the probability function in the first optimization step.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering , vol. 43 no. 4
Type: Research Article
ISSN: 0332-1649

Keywords

Article
Publication date: 2 January 2023

Javad Rahmani Fard, Saadat Jamali Arand and Siroos Hemmati

In this paper, an improved multiobjective particle swarm optimization (PSO) algorithm is proposed to optimize a three-phase, 12-slot, 19-pole, yokeless axial-field flux-switching…

Abstract

Purpose

In this paper, an improved multiobjective particle swarm optimization (PSO) algorithm is proposed to optimize a three-phase, 12-slot, 19-pole, yokeless axial-field flux-switching permanent magnet (YASA-AFFSPM) motor.

Design/methodology/approach

Based on the structural characteristics of the YASA-AFFSPM, a mathematical model is established to calculate the main size of the YASA-AFFSPM motor. The split ratio, stator axial length, sandwiching pole angle, rotor pole angle, PM arc and number of conductors per slot are selected as optimization variables. Also, the efficiency, power factor, cogging torque and average torque are considered as the optimization objectives. The objectives are optimized by combining the improved multiobjective PSO algorithm with electromagnetic calculation.

Findings

Based on the proposed algorithm, the investigated motor is optimized. The on-load efficiency, power factor and average torque of the motor performance have increased by 0.87%, 3.13% and 10.39%, respectively. Moreover, the cogging torque and slot fill factor have undergone decreases of 8.57% and 3.34%, respectively. Finally, the effectiveness of the algorithm is verified using experiment results.

Originality/value

So far, no comprehensive report has been observed on the optimization of the YASA-AFFSPM motor using evolutionary algorithms and the study of the effect of the motor parameters. Therefore, in this paper, the authors decided to investigate the effect of YASA-AFFSPM motor parameters and improve motor performance with the improved PSO method.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering , vol. 42 no. 6
Type: Research Article
ISSN: 0332-1649

Keywords

Article
Publication date: 6 May 2024

Shujing Li, Xiaojuan Huang, Zhiheng He, Yongxiang Liu, Hui Qu and Jing Wu

The purpose of this paper is to introduce a double-stator switched reluctance machine (DS-SRM) for electric vehicles (EVs) and to propose multi-mode operations for this machine.

Abstract

Purpose

The purpose of this paper is to introduce a double-stator switched reluctance machine (DS-SRM) for electric vehicles (EVs) and to propose multi-mode operations for this machine.

Design/methodology/approach

Analysis of flux linkage distributions and torque characteristics using finite element method (FEM). Building a dynamic simulation model based on electromagnetic characteristics, mathematical equations and mechanical motion equations of the DS-SRM drive system. The paper proposes multi-mode operations (inner-stator excitation mode, outer-stator excitation mode and double-stator excitation mode) based on motor working regions. It also conducts simulation and experimental results to verify the effectiveness of the proposed multi-mode operations strategies and control schemes.

Findings

There is almost no electromagnetic coupling between the inner and outer stators due to the specially designed rotor structure and optimized windings polarity configuration. Analysis of flux linkage distributions and torque characteristics verified the independence of inner and outer stators. Proposal of multi-mode operations and corresponding control rules achieved the smooth switching between different modes.

Originality/value

The paper introduced the DS-SRM for EVs and proposed multi-mode operations, along with control rules, to optimize its performance. The specially designed rotor structure, optimized winding polarity configuration, and the proposed multi-mode operations contribute to the originality of the research.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering , vol. 43 no. 2
Type: Research Article
ISSN: 0332-1649

Keywords

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