Design by optimization of an axial-flux permanent-magnet synchronous motor using genetic algorithms

Benlamine, Raouf; Dubas, Frédéric; Randi, Sid; Lhotellier, Dominique; Espanet, Christophe

doi:10.1109/icems.2013.6754546

Cited by 17 publications

(7 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The machine total outer diameter D t is related to the protrusion W cuo of the end windings in the radial direction from the iron core [9] as, = + 2…”

Section: Analytical Sizing Equations Of the Afpmmentioning

confidence: 99%

“…GAs are search methods based on genetics and natural selection [10] and are being applied in the field of design optimization of electric machines [9,14]. In the case of electrical machines design optimization, GA searches the space of the motor parameters emulating genetic reproduction mechanisms, crossover, and mutation with the objective of obtaining an optimal design.…”

Section: The Optimization Functions Dealt Withmentioning

confidence: 99%

“…Therefore, design optimization of electric machines is nowadays receiving much attention as deduced from the number of recently published papers in this topic [9,10]. This paper is focused to obtain an optimal solution among the huge set of possible solutions by using computationally efficient optimization algorithms leading to a global optimum solution while minimizing the computational burden.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimal design of a three-phase AFPM for in-wheel electrical traction

Saavedra

Romeral

Riba

2014

2014 IEEE International Electric Vehicle Conference (IEVC)

View full text Add to dashboard Cite

Abstract-Sinusoidally fed permanent magnet synchronous motors (PMSM) fulfill the special features required for traction motors to be applied in electric vehicles (EV). Among them, axial flux permanent magnet (AFPM) synchronous motors are especially suited for in-wheel applications. Electric motors used in such applications must meet two main requirements, i.e. high power density and fault tolerance. This paper deals with the optimal design of an AFPM for in-wheel applications used to drive an electrical scooter. The single-objective optimization process carried out in this paper is based on designing the AFPM to obtain an optimized power density while ensuring appropriate fault tolerance requirements. For this purpose a set of analytical equations are applied to obtain the geometrical, electric and mechanical parameters of the optimized AFPM and several design restrictions are applied to ensure fault tolerance capability. The optimization process is based on a genetic algorithm and two more constrained nonlinear optimization algorithms in which the objective function is the power density. Comparisons with available data found in the technical bibliography show the appropriateness of the approach developed in this work.

show abstract

“…The machine total outer diameter D t is related to the protrusion W cuo of the end windings in the radial direction from the iron core [9] as, = + 2…”

Section: Analytical Sizing Equations Of the Afpmmentioning

confidence: 99%

Section: The Optimization Functions Dealt Withmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimal design of a three-phase AFPM for in-wheel electrical traction

Saavedra

Romeral

Riba

2014

2014 IEEE International Electric Vehicle Conference (IEVC)

View full text Add to dashboard Cite

show abstract

“…Amaç fonksiyonlarının analitik olarak değerlendirildiği evrimsel optimizasyon, FEM ile karşılaştırıldığında tasarım optimizasyonu için gereken hesaplama süresini önemli ölçüde kısaltmaktadır[11]. yöntemi ile karşılaştırılmıştır[12].Mahmoudi vd. tarafından, genetik algoritma (tabanlı boyutlandırma denklemi ve sonlu elemanlar analizi ile optimize edilmiş bir eksenel akılı sabit mıknatıslı motor sunulmaktadır.…”

unclassified

Genetik Algoritma Metodu Kullanılarak Eksenel Alanlı Kalıcı Mıknatıslı Senkron Makinenin Optimal Tasarımı ve Analizi

PAMUK

2024

JIENS

View full text Add to dashboard Cite

Eksenel alanlı kalıcı mıknatıslı senkron makineler yüksek güç yoğunluğu ve karmaşık yapısı olmasından dolayı elektrik sistemi içerisinde önemli avantajlar sunmaktadır ve bu nedenlerle birçok uygulama alanı bulunmaktadır. Senkron makine tasarım sürecinin özü, makine özelliklerinin hızlı, esnek ve doğru hesaplanmasına bağlıdır. Tahrik gereksinimlerini karşılamak ve doğrulamasını gerçekleştirebilmek için elektromanyetik tork analizinin yapılması gerekmektedir. Elektromanyetik tork analizi için birçok farklı yöntem kullanılmaktadır. Bu çalışmada, genetik algoritma optimizasyon teorisi kullanılarak, eksenel alanlı kalıcı mıknatıslı senkron makinenin optimal tasarımı ve analizi gerçekleştirilmiştir. Eksenel alanlı kalıcı mıknatıslı senkron makinenin optimal tasarımı için gerekli olan matematiksel model yapısı oluşturulmuştur. Eksenel alanlı kalıcı mıknatıslı senkron makine tasarımındaki kritik değerlerin belirlenmesine yönelik genetik algoritma optimizasyon yöntemi ile literatürde kullanılan farklı yöntemler birbirleri ile karşılaştırılmıştır. Yapılan çalışmalardan elde edilen sonuçların birbirine yakın olması, makine tasarımındaki kritik değerlerin hesaplanmasında genetik algoritma optimizasyon yönteminin potansiyelini ortaya koymaktadır. Çalışmadan elde edilen genetik algoritma optimizasyon sonuçları ile, eksenel alanlı kalıcı mıknatıslı senkron makinenin optimal tasarımında kullanılan kritik değerlerin daha kolay belirlenebileceği gösterilmiştir.

show abstract

“…The decision to use those two optimisation techniques is based on the good performance of the selected methods in other or similar optimisation procedures found in literature, from which only selected works are presented. (Benlamine et al, 2013;Chitara et al, 2018;Eom et al, 2001;Kumar and Chakarverty, 2011;Mirahki et al, 2014;Uler et al, 1995). GA was quite successfully also used in the optimisation of the cogging torque using different approaches.…”

mentioning

confidence: 99%

Selected Nature-Inspired Algorithms in Function of PM Synchronous Motor Cogging Torque Minimisation

Cvetkovski

Petkovska

2021

Power Electronics and Drives

View full text Add to dashboard Cite

Both permanent magnet brushless DC motors and permanent magnet synchronous motors have attracted wide attention and are increasingly used in industrial high-performance applications in recent years. Those motors are known for their good electrical, magnetic and performance characteristics, but there is one parameter known as cogging torque that has a negative influence on the performance characteristics of the motor. This pulsating torque is generated as a result of the interaction between the stator teeth and the permanent magnets. The minimisation of the ripple of this torque in those permanent magnet motors is of great importance and is generally achieved by a special motor design which in the design process involves a variety of many geometrical motor parameters. In this research work, a novel approach will be introduced where two different nature-inspired algorithms, such as genetic algorithm (GA) and cuckoo search (CS) algorithm are used as an optimisation tool, in which the defined equation for the maximum value of the cogging torque is applied as an objective function. Therefore, a proper mathematical presentation of the maximum value of the cogging torque for the analysed synchronous motor is developed and implemented in the research work. For a detailed analysis of the three different motor models, the initial motor and the two optimised motor models are modelled and analysed using a finite element method approach. The cogging torque is analytically and numerically calculated and the results for all the models are presented.

show abstract

Design by optimization of an axial-flux permanent-magnet synchronous motor using genetic algorithms

Cited by 17 publications

References 5 publications

Optimal design of a three-phase AFPM for in-wheel electrical traction

Optimal design of a three-phase AFPM for in-wheel electrical traction

Genetik Algoritma Metodu Kullanılarak Eksenel Alanlı Kalıcı Mıknatıslı Senkron Makinenin Optimal Tasarımı ve Analizi

Selected Nature-Inspired Algorithms in Function of PM Synchronous Motor Cogging Torque Minimisation

Contact Info

Product

Resources

About