Design optimization of APMEC using chaos multi-objective particle swarm optimization algorithm

In order to meet the requirement that the permanent magnet eddy current coupler has larger output torque and smaller eddy current loss in actual operation, the structural parameters and operation performance of axial permanent magnet eddy current coupler (APMEC) are optimized by chaos multi-objectiv...

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Autores principales:	Pengyi Pan, Dazhi Wang, Bowen Niu
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Axial permanent magnet eddy current coupler Finite element method (FEM) Response surface methodology (RSM) Chaos multi-objective particle swarm optimization algorithm Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/1fe830997cfc42859f636ff19b2f0074
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spelling	oai:doaj.org-article:1fe830997cfc42859f636ff19b2f00742021-11-26T04:32:16ZDesign optimization of APMEC using chaos multi-objective particle swarm optimization algorithm2352-484710.1016/j.egyr.2021.08.009https://doaj.org/article/1fe830997cfc42859f636ff19b2f00742021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2352484721006090https://doaj.org/toc/2352-4847In order to meet the requirement that the permanent magnet eddy current coupler has larger output torque and smaller eddy current loss in actual operation, the structural parameters and operation performance of axial permanent magnet eddy current coupler (APMEC) are optimized by chaos multi-objective particle swarm optimization algorithm (CMOPSO) in this paper. The model of APMEC is established by three-dimensional finite element simulation. The central composite design (CCD) method is used to select the appropriate test point, and the response value is obtained by ANSYS finite element analysis software simulation. The second-order response surface regression model of APMEC was established according to the response value. The CMOPSO is used to optimize APMEC, and the optimal combination of structural parameters is obtained. By comparing the eddy current density distribution of APMEC before and after optimization with the finite element simulation experiment, it is verified that the optimization method is feasible to optimize the structural parameters of APMEC. The optimization results show that the efficiency of the permanent magnet eddy current coupler is more than 94%, and the energy consumption is reduced to 83% of the original energy consumption.Pengyi PanDazhi WangBowen NiuElsevierarticleAxial permanent magnet eddy current couplerFinite element method (FEM)Response surface methodology (RSM)Chaos multi-objective particle swarm optimization algorithmElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENEnergy Reports, Vol 7, Iss , Pp 531-537 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Axial permanent magnet eddy current coupler Finite element method (FEM) Response surface methodology (RSM) Chaos multi-objective particle swarm optimization algorithm Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Axial permanent magnet eddy current coupler Finite element method (FEM) Response surface methodology (RSM) Chaos multi-objective particle swarm optimization algorithm Electrical engineering. Electronics. Nuclear engineering TK1-9971 Pengyi Pan Dazhi Wang Bowen Niu Design optimization of APMEC using chaos multi-objective particle swarm optimization algorithm
description	In order to meet the requirement that the permanent magnet eddy current coupler has larger output torque and smaller eddy current loss in actual operation, the structural parameters and operation performance of axial permanent magnet eddy current coupler (APMEC) are optimized by chaos multi-objective particle swarm optimization algorithm (CMOPSO) in this paper. The model of APMEC is established by three-dimensional finite element simulation. The central composite design (CCD) method is used to select the appropriate test point, and the response value is obtained by ANSYS finite element analysis software simulation. The second-order response surface regression model of APMEC was established according to the response value. The CMOPSO is used to optimize APMEC, and the optimal combination of structural parameters is obtained. By comparing the eddy current density distribution of APMEC before and after optimization with the finite element simulation experiment, it is verified that the optimization method is feasible to optimize the structural parameters of APMEC. The optimization results show that the efficiency of the permanent magnet eddy current coupler is more than 94%, and the energy consumption is reduced to 83% of the original energy consumption.
format	article
author	Pengyi Pan Dazhi Wang Bowen Niu
author_facet	Pengyi Pan Dazhi Wang Bowen Niu
author_sort	Pengyi Pan
title	Design optimization of APMEC using chaos multi-objective particle swarm optimization algorithm
title_short	Design optimization of APMEC using chaos multi-objective particle swarm optimization algorithm
title_full	Design optimization of APMEC using chaos multi-objective particle swarm optimization algorithm
title_fullStr	Design optimization of APMEC using chaos multi-objective particle swarm optimization algorithm
title_full_unstemmed	Design optimization of APMEC using chaos multi-objective particle swarm optimization algorithm
title_sort	design optimization of apmec using chaos multi-objective particle swarm optimization algorithm
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/1fe830997cfc42859f636ff19b2f0074
work_keys_str_mv	AT pengyipan designoptimizationofapmecusingchaosmultiobjectiveparticleswarmoptimizationalgorithm AT dazhiwang designoptimizationofapmecusingchaosmultiobjectiveparticleswarmoptimizationalgorithm AT bowenniu designoptimizationofapmecusingchaosmultiobjectiveparticleswarmoptimizationalgorithm
_version_	1718409827301982208

Design optimization of APMEC using chaos multi-objective particle swarm optimization algorithm

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