Brushless Motor Performance Optimization by Eagle Strategy with Firefly and PSO
نویسندگان
چکیده
منابع مشابه
Multi-Objective Design Optimization of a Linear Brushless Permanent Magnet Motor Using Particle Swarm Optimization (PSO)
In this paper a brushless permanent magnet motor is designed considering minimum thrust ripple and maximum thrust density (the ratio of the thrust to permanent magnet volumes). Particle Swarm Optimization (PSO) is used as optimization method. Finite element analysis (FEA) is carried out base on the optimized and conventional geometric dimensions of the motor. The results of the FEA deal to ...
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Most global optimization problems are nonlinear and thus difficult to solve, and they become even more challenging when uncertainties are present in objective functions and constraints. This paper provides a new two-stage hybrid search method, called Eagle Strategy, for stochastic optimization. This strategy intends to combine the random search using Lévy walk with the firefly algorithm in an i...
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Despite many advantages of BrushLess DC motor, torque pulsation is one of the most important disadvantages of it. At first, an optimum primary design of BLDC motor is done using PSO algorithm. Then, other parameters for reducing the torque pulsation are considered by finite element method. It is shown that fractional slot structure has many advantages than conventional one. Both cogging and rip...
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Abstract: A new type of permanent magnet (PM) brushless claw pole motor (CPM) with soft magnetic composite (SMC) core is designed and analyzed in this paper. The PMs are mounted on the claw pole surface, and the three-phase stator windings are fed by variable-frequency three-phase AC currents. The advantages of the proposed CPM are that the slip rings on the rotor are cast off and it can achiev...
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ژورنال
عنوان ژورنال: International Journal of Engineering Trends and Technology
سال: 2020
ISSN: 2231-5381
DOI: 10.14445/22315381/ijett-v68i9p220