2017
DOI: 10.1109/tie.2017.2708038
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Design of a Permanent Magnet Synchronous Generator Using Interactive Multiobjective Optimization

Abstract: This is a self-archived version of an original article. This version may differ from the original in pagination and typographic details.

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Cited by 36 publications
(23 citation statements)
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References 24 publications
(36 reference statements)
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“…In [17], authors use a multi-physics model comprising six sub-models that are electrical, magnetic, thermal, mechanical, geometrical, and economical to design an optimum 55kW PMSG. Several optimization methods are presented in the literature for designing PM synchronous machines such as Sequential-Stage strategy [18], Interactive multi-objective [19], Monte Carlo [20], and Multi-Objective Genetic Algorithm [21].…”
Section: Introductionmentioning
confidence: 99%
“…In [17], authors use a multi-physics model comprising six sub-models that are electrical, magnetic, thermal, mechanical, geometrical, and economical to design an optimum 55kW PMSG. Several optimization methods are presented in the literature for designing PM synchronous machines such as Sequential-Stage strategy [18], Interactive multi-objective [19], Monte Carlo [20], and Multi-Objective Genetic Algorithm [21].…”
Section: Introductionmentioning
confidence: 99%
“…At present, the energy development in the world is mostly hydraulic power generation, thermal power generation, wind power generation and so on. In modern power industry, synchronous generator is the most commonly used alternator, which is widely used in thermal power generation, diesel engine power generation, nuclear power generation, and so on [1][2][3]. During the operation of synchronous generators, there are many system uncertainties and serious external disturbances.…”
Section: Introductionmentioning
confidence: 99%
“…IGH performance permanent magnet synchronous motors are of high demand in industrial applications like electric vehicle due to the requirements of high efficiency, low cost, low acoustic noise and smooth torque [1][2][3].…”
Section: Introductionmentioning
confidence: 99%
“…During the past years, particle swarm optimization (PSO) have been used, e.g., in [10] and [12], genetic algorithm (GA) optimization method in [3] and [9]. There are also some new optimization strategies [1] and [2]. In [10], a modified PSO is proposed to search the cost value of the global best during in the current iteration.…”
Section: Introductionmentioning
confidence: 99%