Optimal Design of Permanent-Magnet Motors For Electric Vehicles by using Particle Swarm Optimization Algorithm

سال انتشار: 1395
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 483

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شناسه ملی سند علمی:

ICRSIE01_701

تاریخ نمایه سازی: 25 آذر 1395

چکیده مقاله:

In this paper, the particle swarm optimization (PSO) algorithm is applied to the multi objective optimum design of the surface mounted permanent magnet synchronous motor. The optimum design procedure for electric vehicle application is divided into two steps. First, the losses and the cost are minimized, and the power density is maximized by optimizing both the dimension and the flux density distribution of the stator with an analytical model. Second, constraints such as temperature rise, saturation and demagnetization are satisfied. In order to verify the validity of the proposed method, the PSO method, the modified Hooke-Jeeves optimization method and the augmented Lagrangian method are compared to optimize three PM motors with different rated powers: 5.75 (kw), 3.77 (kw) and 188.5 (kw). This comparison is based on some features such as losses, cost and power density. The obtained results demonstrate that the PSO method is faster and more efficient than other two methods.

کلیدواژه ها:

Particle swarm optimization algorithm ، permanent magnet synchronous motors ، electrical vehicle ، multi objective optimum

نویسندگان

Mohammad Mohammadrezaei

Electrical and Computer Engineering Department, University of Zanjan, Zanjan,Iran,

Reza Noroozian

Electrical and Computer Engineering Department, University of Zanjan, Zanjan, Iran,

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