Optimized design of induction motor parameters based on PSO (Particle Swarm Optimization)

Guo, Ping; Huang, Dagui; Feng, Daiwei; Yu, Wenzheng; Zhang, Hailong

doi:10.1109/icma.2012.6283251

Cited by 5 publications

(3 citation statements)

References 4 publications

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“…Above those literatures, the improved methods mainly come from fitness function and combination with other algorithms, regardless of the searching step and searching precision for particles. Linear method of inertia coefficient is proposed in [7]. This modified method has improved the optimized performance in consideration of the searching step and searching precision for particles in a degree.…”

Section: Introductionmentioning

confidence: 99%

A New Method of Speed Control for Induction Motor Based On Improved Particle Swarm Optimization

Yi¹,

Sui²,

Yu³

2016

JCTECS

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Abstract-Optimization techniques are becoming more popular for the improvement in control of induction motor. Many intelligent algorithms have been used to improve performance of induction motor so for including particle swarm optimization. However, the improved performance may be limited on account of inertia coefficient in particle swarm optimization, which lead to the unbalance between the searching step and searching precision. In this paper, a variable-step nonlinear dynamic inertia weight of particle swarm optimization speed controller is proposed to improve the performance of an induction motor. The experiment results show that the proposed method has excellent performance.

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Section: Introductionmentioning

confidence: 99%

A New Method of Speed Control for Induction Motor Based On Improved Particle Swarm Optimization

Yi¹,

Sui²,

Yu³

2016

JCTECS

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“…Optimization of braking energy is a nonlinear problem; it is suitable to examine heuristic optimization techniques to solve this problem. PSO is used extensively to design, control and operate three phase induction motor [8][9][10][11]. The rule of the PSO in this paper is to find the suitable variation of voltage and frequency during a certain braking period to minimize energy losses in the motor, this will result in less heat and allow for frequent braking in a certain time.…”

Section: Introductionmentioning

confidence: 99%

Braking of Three Phase Induction Motors by Controlling Applied Voltage and Frequency Based on Particle Swarm Optimization Technique

Elkholy

El‐Hameed

2015

IJPEDS

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Braking of three phase induction motors is required in many industrial applications. This paper introduces braking of three phase induction motors using particle swarm optimization (PSO) technique. The objective is to determine the optimum values of the applied voltage and frequency during braking to stop the motor in a certain time with minimum braking energy losses to limit any excessive thermal heating. The proposed technique is important and more useful in applications of repeated braking cycles. The results are compared with that obtained using plugging braking method and it's found that the proposed technique gives lower braking energy and shorter braking time. The braking energy losses with the proposed method are about 20% of the plugging braking energy losses with the same braking time. The proposed method determines the variation of optimal values of applied voltage and frequency to have a certain braking time of three phase induction motor at a certain load torque with minimum braking energy losses. The characteristics of the motor are simulated using SIMULINK/MATLAB.

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“…An PSObased optimal design of axial laminated synchronous reluctance motor (SynRM) has been used for traction applications [20]. Moreover, designs of induction machines using PSO method have also been reported [21]. This paper concerns the design of a 500W AFPM generator for small-scale wind power system.…”

Section: Introductionmentioning

confidence: 99%

Particle Swarm Optimization of Air-cored Axial Flux Permanent Magnet Generator for Small-scale Wind Power Systems

Xia

Luk

Fei

et al. 2014

7th IET International Conference on Power Electronics, Machines and Drives (PEMD 2014)

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Axial flux permanent magnet synchronous machines with aircored configuration is particular suitable for small scale wind power system due to their advantages of low synchronous reactance, cogging torque free, high efficiency and high power factor. However, due to the number of machine parameters, with some tightly 'coupled' with each other, optimisation of the design could become extremely challenging by conventional analytical means. Here, the particle swarm optimization method is used in the design of an axial flux permanent magnet generator for small-scale wind power system. Five inter-dependent design parameters are adjusted simultaneously to achieve an optimal solution for the application. Three-dimensional finite element analysis is employed to evaluate the electromagnetic performance for the optimization. The results show the proposed optimization method is efficient and with fast convergence.

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Optimized design of induction motor parameters based on PSO (Particle Swarm Optimization)

Cited by 5 publications

References 4 publications

A New Method of Speed Control for Induction Motor Based On Improved Particle Swarm Optimization

A New Method of Speed Control for Induction Motor Based On Improved Particle Swarm Optimization

Braking of Three Phase Induction Motors by Controlling Applied Voltage and Frequency Based on Particle Swarm Optimization Technique

Particle Swarm Optimization of Air-cored Axial Flux Permanent Magnet Generator for Small-scale Wind Power Systems

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