Magnetic levitation flywheel motor structure parameter optimization design method

Abstract

The invention discloses a magnetic levitation flywheel motor structure parameter optimization design method, which mainly comprises the steps of establishing a motor finite element model, and determining motor optimization performance parameters; establishing a response surface experiment arrangement table; obtaining response values of the motor torque and the suspension output under each parameter combination; establishing a polynomial response surface model FRSM; calculating and recording error data between the FRSM fitting value and the finite element value; establishing an error non-parametric response surface model FSVM by using a support vector machine; obtaining each performance output model of the final motor; establishing a comprehensive multi-objective optimization function fobj;and obtaining the optimal structure parameters of the motor by using a firefly algorithm. According to the invention, a traditional polynomial response surface and a non-parametric response surface model based on a support vector machine are combined to establish a dynamic dual-response surface model between motor output performance and structural parameters, and a firefly algorithm is used to carry out global optimization on the structure parameters, so rapid and accurate modeling under small sample data and motor multi-output performance collaborative optimal parameter design are realized.

Description

technical field [0001] The invention relates to the technical field of magnetic levitation motors, in particular to a method for optimizing the structural parameters of a magnetic levitation flywheel motor. Background technique [0002] Flywheel energy storage is an emerging physical energy storage method, which has the advantages of high efficiency, long life, and high power density, and has broad application prospects in distributed power supplies, hybrid vehicles, and other fields. The magnetic levitation switched reluctance motor combines the dual advantages of magnetic bearings and switched reluctance motors, and introduces it into the flywheel energy storage to form a magnetic levitation flywheel motor (Bearinglessflywheel Machine, BFM), which can simplify the system structure, improve the critical speed and reliability. unique advantages in this field. However, in practice, high-speed operation and suspension support problems restrict its popularization and applicati...

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Problems solved by technology

[0005] Purpose of the invention: Aiming at the shortcomings of the modeling and multi-objective optimization methods of the maglev flywheel motor in the prior art, the present invention discloses a method for optimizing the structural parameters of the maglev flywheel motor, which is formed by combining the traditional second-order polynomial and the SVM non-parametric response surface method Dynamic Dual Response Surface Method (DRSM) is used to establish a mathematical model between motor performance and structural parameters. While ensuring the accuracy of the solution, it can greatly reduce the calculation cost of the finite element model, realize fast and accurate modeling under small sample data, and effectively Improve the problem of low fitting accuracy of traditional RSM for complex relationships with high-order interactions

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