Multi-objective structure optimization method of magnetic gear brushless direct current motor

A technology of brushing DC motor and optimization method, applied in the field of electric drive

Active Publication Date: 2019-07-12
SUZHOU VOCATIONAL UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

After retrieving relevant patents and literature at home and abroad, there is no chaos search reverse learnin...

Method used

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  • Multi-objective structure optimization method of magnetic gear brushless direct current motor
  • Multi-objective structure optimization method of magnetic gear brushless direct current motor
  • Multi-objective structure optimization method of magnetic gear brushless direct current motor

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Embodiment Construction

[0048] Below in conjunction with accompanying drawing, technical scheme of the present invention is described in further detail:

[0049] Embodiment 1 provides a multi-objective structure optimization method for a magnetic gear brushless DC motor, comprising the following steps:

[0050] The steps of the chaotic search reverse learning difference method can be briefly described as follows:

[0051] Step S1, initialization

[0052]Select the number of stator slots, the number of rotor slots, the outer diameter of the rotor end ring, and the inner diameter of the rotor end ring among the structural parameters of the magnetic gear brushless DC motor as the structural parameters, and generate the first four groups at the same time; choose any structural parameter as one of the groups, Initially, the group generation method is to start randomly in the search space, and its progress is as follows:

[0053]

[0054] In formula (1), is the initial group, σ i ∈(0,1] random numb...

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Abstract

The invention discloses a multi-objective structure optimization method of a magnetic gear brushless direct current motor. The method takes volume minimization and efficiency maximization as optimization objectives, takes current, slip frequency, magnetic flux density, power factors and other related limiting conditions into consideration in the analysis process, and selects the number of stator slots, the number of rotor slots, the outer diameter of a rotor end ring and the inner diameter of a rotor end ring as optimization objects, so that the performance of the magnetic gear brushless direct current motor system is improved. The method mainly comprises the steps that chaotic search is concentrated in a chaotic search reverse learning difference method, and the reverse learning method isfused into a difference evolution method; the search capability of the differential evolution method can be improved, and only two control parameters need to be specified, so that the chaotic searchreverse learning differential method has robustness, and the framework has an online parameter adjustment capability, has a better structural optimization capability for the magnetic gear brushless direct current motor, and can effectively improve the dynamic characteristics of a driving system.

Description

technical field [0001] The invention relates to the technical field of electric power transmission, in particular to a multi-objective structure optimization method of a magnetic gear brushless DC motor. Background technique [0002] Compared with mechanical gears, magnetic gears have the advantages of low noise, high efficiency, easy maintenance, high reliability and overload protection. Magnetic gears are widely used in the field of electric transmission such as high force density drives, and are especially suitable for occasions that require no lubrication, no noise, no frictional energy consumption, no oil, and are waterproof and dustproof. The magnetic gear and brushless DC motor are integrated into a magnetic gear brushless DC motor, which is used in electric vehicles and has high power density and high torque density, wide speed range, including low speed climbing and high speed driving, high efficiency, wide Constant power area and constant speed area, high reliabil...

Claims

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Application Information

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IPC IPC(8): G06F17/50
CPCG06F30/23Y02T10/64
Inventor 杨益飞汪红兵黄海洋
Owner SUZHOU VOCATIONAL UNIV
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