An optimal material distribution design of Brushless DC motor by genetic algorithm considering a cluster of material

Ishikawa, Masatoshi; Yonetake,; Kurita,

doi:10.1109/cefc.2010.5481675

Cited by 4 publications

(4 citation statements)

References 2 publications

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“…However, there are some important design constraints for in-wheel BLDCMs, mainly relating to the dimensions of the driving wheel, where the BLDCM is located, with considerations of the size of the tire and the braking system. These constraints directly affect the parts of a BLDC motor, such as the size of the magnet, back iron depth and air gap [5][6][7]. Analytical studies that can help determine the geometric dimensions of a BLDCM that affect the output parameters, such as efficiency and torque, can also be found in the literature [8].…”

Section: Introductionmentioning

confidence: 99%

In Search of the Proper Dimensions of the Optimum In-Wheel Permanent Magnet Synchronous Motor Design

Cabuk,

Ustun

2024

Energies

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In this paper, a new approach to the optimized design of outer rotor Permanent Magnet Synchronous Motors (PMSMs) for in-wheel light electric vehicle (LEV) applications is presented. The optimized design study is based on various dimensions such as back iron depth, permanent magnet depth and air gap length. The novel method is developed to reveal the quality factor of design (QFD), which implies the maximum possible performance results, and determine the best possible design for in-wheel PMSMs for direct-drive LEV applications. Therefore, the thickness of the back iron, permanent magnet and air gap dimensions are altered accordingly to obtain an optimized design. This design study is conducted for an in-wheel PMSM that has rated values of 2.5 kW, 150 V, 900 min−1, and 24-slot/20-pole configuration intended for LEV propulsion. These designs are simulated in order to obtain the maximized combination of efficiency, shaft power, shaft torque and a minimized combination of total weight, iron losses, copper losses, input current and cogging torque. The measure of the optimized parameters is named QFD, which indicates the goodness of the design through the use of radar charts. The values of the essential coefficients of QFD may vary for different applications, e.g., the design of PMSMs used in traction applications has some certain criteria that imply high-performance operation. Additionally, the QFD can guide motor manufacturers as a starting point for a design study.

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Section: Introductionmentioning

confidence: 99%

In Search of the Proper Dimensions of the Optimum In-Wheel Permanent Magnet Synchronous Motor Design

Cabuk,

Ustun

2024

Energies

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“…On the contrary, in literature different papers have been devoted on scalar optimization referred to PMFS or other categories of PM machines. Genetic algorithm (GA) is developed for topology optimization of the stator teeth in a brushless DC motor in [35]. In [36] optimal design of interior permanent magnet synchronous (IMPS) machine is developed based on combination of GA and mesh adoptive guided search.…”

Section: Introductionmentioning

confidence: 99%

Optimal design of permanent magnet flux switching generator for wind applications via artificial neural network and multi-objective particle swarm optimization hybrid approach

Meo

Zohoori

Vahedi

2016

Energy Conversion and Management

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“…They showed that their proposed algorithm can reveal a better performance in comparison with Electromagnetic-like Algorithm (EMA). Another discussion about optimization tools to solve the BLDC was proposed by Ishikawa et al, [13]. They considered a new GA based on the topology optimization to solve the stator teeth in a BLDC motor to minimize torque ripple.…”

Section: Introductionmentioning

confidence: 99%

An Improved Red Deer Algorithm to Address a Direct Current Brushless Motor Design Problem

2019

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The Red Deer Algorithm (RDA) is one of recent metaheuristic algorithms inspired by the behavior of red deers during a breading season. The RDA revealed its performance for a variety of combinatorial optimization problems in different real-world applications. In this paper, the parameters and operators of RDA using some adaptive strategies have been modified to improve the performance of this optimizer. To prove the efficiency of Improved RDA (IRDA), not only some benchmarked functions are utilized but also a Direct Current (DC) brushless motor design as one of real-world engineering design issues. The results of developed IRDA are compared with its general idea and existing algorithms from the literature. This comparative study confirms that the offered IRDA outperforms the other algorithms and provide very competitive results.

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An optimal material distribution design of Brushless DC motor by genetic algorithm considering a cluster of material

Cited by 4 publications

References 2 publications

In Search of the Proper Dimensions of the Optimum In-Wheel Permanent Magnet Synchronous Motor Design

In Search of the Proper Dimensions of the Optimum In-Wheel Permanent Magnet Synchronous Motor Design

Optimal design of permanent magnet flux switching generator for wind applications via artificial neural network and multi-objective particle swarm optimization hybrid approach

An Improved Red Deer Algorithm to Address a Direct Current Brushless Motor Design Problem

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