LAPSE:2023.6761v1
Published Article
LAPSE:2023.6761v1
Design and Optimization Method with Independent Radial and Axial Capacity for 3-DOF Magnetic Bearings in Flywheel
Jintao Ju, Peng Xu, Shuqing Li, Tong Xu, Fangming Ju, Jiahui Du
February 24, 2023
Abstract
The six-pole radial−axial hybrid magnetic bearing (RAHMB) has the advantages of small space and low power consumption, making it suitable for flywheel batteries. The bearing capacity and the volume are the main specifications of magnetic bearings that should be considered comprehensively. In this work, the six-pole RAHMB was used in a horizontal flywheel battery. As the axial bearing capacity is relatively smaller than the radial bearing capacity, a design method with independent radial and axial bearing capacity is proposed, and the parameters are optimized to minimize the volume. The mathematical model of six-pole RAHMB was derived from the equivalent magnetic circuit method. The relationships between bearing capacity, biased flux density, saturation flux density and the section area of magnetic poles were analyzed. The basic principle of the design method with independent radial and axial bearing capacity is to determine which five of the variables are preferred. According to the design method, one radial or axial biased flux density should be optimized to minimize the volume, and the genetic algorithm (GA) was adopted to search for the optimal value. The structural parameters were designed based on the optimized value of biased flux density. The total volume of the six-pole RAHMB was reduced by 24%. A 3D finite element (FE) model was built. The analysis results and experimental results show that the proposed design and the optimization method are feasible and valid.
Keywords
flywheel battery, Genetic Algorithm, Optimization, six-pole radial–axial hybrid magnetic bearing
Suggested Citation
Ju J, Xu P, Li S, Xu T, Ju F, Du J. Design and Optimization Method with Independent Radial and Axial Capacity for 3-DOF Magnetic Bearings in Flywheel. (2023). LAPSE:2023.6761v1
Author Affiliations
Ju J: School of Electrical and Information Engineering, Changzhou Institute of Technology, Changzhou 212031, China
Xu P: School of Mechanical Engineering and Rail Transit, Changzhou University, Changzhou 213164, China
Li S: School of Electrical and Information Engineering, Changzhou Institute of Technology, Changzhou 212031, China
Xu T: School of Electrical and Information Engineering, Changzhou Institute of Technology, Changzhou 212031, China
Ju F: School of Electrical and Information Engineering, Changzhou Institute of Technology, Changzhou 212031, China
Du J: School of Electrical and Information Engineering, Changzhou Institute of Technology, Changzhou 212031, China
Journal Name
Energies
Volume
16
Issue
1
First Page
483
Year
2023
Publication Date
2023-01-01
ISSN
1996-1073
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Original Submission
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PII: en16010483, Publication Type: Journal Article
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LAPSE:2023.6761v1
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https://doi.org/10.3390/en16010483
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Feb 24, 2023
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