Design and prototyping of an optimised axial‐flux permanent‐magnet synchronous machine

Mahmoudi, Amin; Kahourzade, Solmaz; Rahim, N.A.; Ping, Hew Wooi; Uddin, M. Nasir

doi:10.1049/iet-epa.2012.0377

Cited by 44 publications

(26 citation statements)

References 29 publications

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“…Currently, most small wind turbines use a PMSG because it has a high efficiency and energy density and is able to deliver reactive power [16], allowing the use of a passive diode rectifier. The mechanical input power P m of the PMSG can be calculated by:…”

Section: Permanent Magnet Synchronous Generatormentioning

confidence: 99%

Displacement of the maximum power point caused by losses in wind turbine systems

et al. 2016

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Keywords:Wind energy Maximum power point tracking Modeling of losses Power coefficient Energy yield a b s t r a c tThe energy yield of wind turbines is to a large extent determined by the performance of the Maximum Power Point Tracking (MPPT) algorithm. Conventionally, they are programmed to maximize the turbines power coefficient. However, due to losses in the generator and converter, the true optimal operating point of the system shifts. This effect is often overlooked, which results in a decreased energy yield. Therefore, in this paper, the wind turbine system is modeled including the dominant loss components to investigate this effect in detail. By simulations and experiments on a wind turbine emulator, it is shown that the location of the maximum power point is significantly affected for low wind speeds. For high wind speeds, the effect is less pronounced. The parameter of interest is the increase in yearly energy output with respect to the classical MPPT method, which is calculated in this paper by including a Rayleigh wind speed distribution. For typical average wind speeds, the energy yield can increase with 1 e2%. There is no cost associated with operating the turbine in the overall MPP, making it worthwhile to include this effect. The findings are implemented in an MPPT algorithm to validate the increased performance in a dynamic situation.

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Section: Permanent Magnet Synchronous Generatormentioning

confidence: 99%

Displacement of the maximum power point caused by losses in wind turbine systems

et al. 2016

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“…On the other hand, the genetic algorithm (GA) [8][9][10] is an intelligent stochastic search algorithm, which has robust global searching ability. This could fill the gap of the Taguchi method in the optimal design of motors.…”

Section: Introductionmentioning

confidence: 99%

A novel hybrid genetic algorithm for optimal design of IPM machines for electric vehicle

Wang

Guo

2017

Open Physics

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A novel hybrid genetic algorithm (HGA) is proposed to optimize the rotor structure of an IPM machine which is used in EV application. The finite element (FE) simulation results of the HGA design is compared with the genetic algorithm (GA) design and those before optimized. It is shown that the performance of the IPMSM is effectively improved by employing the GA and HGA, especially by HGA. Moreover, higher flux-weakening capability and less magnet usage are also obtained. Therefore, the validity of HGA method in IPMSM optimization design is verified.

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“…However, compare to the ironless electricity generator, it has much lower starting torque, higher efficiency and can produce a considerable amount of electricity based on the size of the generator itself. This type of generator has no cogging effect and low CEMF resistance [2] during the operation to produce the electricity. It is because the generator itself does not have the iron core lamination that can be found in the iron-cored and coreless electricity generator.…”

Section: Introductionmentioning

confidence: 99%

Preliminary Studies on Number of Coil Turns per Phase and Distance between the Magnet Pairs for AFPM Ironless Electricity Generator

Leong

Razali

Priyandoko

et al. 2016

MATEC Web of Conferences

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Abstract. The generator that normally used in the market, which is the iron-cored electricity generator has high cogging and starting torques. By redesigning of the iron-cored electricity generator, Axial-flux Permanent Magnet (AFPM) configuration minimizes the usage of ferrite material. AFPM, one of the coreless electricity generator configuration has a less counter electromotive force (CEMF) compare to the cored electricity generator. AFPM configuration also has no cogging torque and low starting torque. Application of a coreless electricity generator is the most suitable compare to the cored electricity generator. However, it is expected that the elimination of the ferrite material within the coreless electricity generator itself increases the power generation. The configuration is the ironless electricity generator. This paper presents the design and analysis of the AFPM ironless electricity generator. There are two main parameters present in this paper, different number of turns of coil per phase and distance between a pair of the magnet. The result of the analysis shows that when the coil turns per phase increased, the voltage output and magnetic flux within the coil also increased. While increasing the distance between the magnets, the voltage output, and magnetic flux within the coil decreases.

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Design and prototyping of an optimised axial‐flux permanent‐magnet synchronous machine

Cited by 44 publications

References 29 publications

Displacement of the maximum power point caused by losses in wind turbine systems

Displacement of the maximum power point caused by losses in wind turbine systems

A novel hybrid genetic algorithm for optimal design of IPM machines for electric vehicle

Preliminary Studies on Number of Coil Turns per Phase and Distance between the Magnet Pairs for AFPM Ironless Electricity Generator

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