Multi‑objective parameter optimization for axial‑radial integrated electromagnetic levitation transport device

Dongning Liu; Jiaqi Yu; Chuan Zhao; Feng Sun; Siqi Li

Multi‑objective parameter optimization for axial‑radial integrated electromagnetic levitation transport device

Vol. 25, No. 11, pp. 2041-2050, Nov. 2025

10.1007/s43236-025-01034-0

Axial-radial integrated magnetic levitation

Pipeline transportation

Displacement stiffness

Multi-objective optimization

Abstract

Aiming at the problems of high cost, high power consumption, and high heat generation in existing electromagnetic levitation transportation systems, an Axial-Radial Integrated Electromagnetic Levitation Transport Device (AIELT) is proposed in this paper. Since the axial and radial integrated levitation mode of the AIELT converts the radial magnetic field of the magnetic column into an axial magnetic field to form axial levitation force, there exists a contradictory problem where it is difficult to enhance both levitation and axial stiffness simultaneously. For this reason, an optimization algorithm is utilized to perform multi-objective parameter optimization of the structural parameters, affecting both the levitation and axial stiffness of the AIELT. First, correlation analysis is utilized to compare the influence of structural parameters on the optimization objectives, distinguishing between the primary and secondary optimization parameters based on the correlation coefficient. Subsequently, a prediction model of the levitation and axial stiffness of the AIELT is established by combining the Brain Storm Optimization Algorithm (BSO) with the Back Propagation (BP) neural network to analyze the relationship between each of the parameters and the objectives, obtaining a fitness functional relationship. Finally, the Multi-Objective Particle Swarm Algorithm (MOPSO) algorithm is utilized to further refine the model and select the final optimized parameter values. Finite element simulations and experiments demonstrate that the proposed model obtains the optimization results accurately, and significantly enhances the stiffness and magnetic properties of the overall AIELT system. Additionally, it enables stable levitation of the object in 5-DOF with the control of the axial and radial levitation integrated structure.

Statistics

Show / Hide Statistics

Cumulative Counts from September 30th, 2019
Multiple requests among the same browser session are counted as one view. If you mouse over a chart, the values of data points will be shown.

Cite this article

[IEEE Style]

D. Liu, J. Yu, C. Zhao, F. Sun, S. Li, "Multi‑objective parameter optimization for axial‑radial integrated electromagnetic levitation transport device," Journal of Power Electronics, vol. 25, no. 11, pp. 2041-2050, 2025. DOI: 10.1007/s43236-025-01034-0.

[ACM Style]

Dongning Liu, Jiaqi Yu, Chuan Zhao, Feng Sun, and Siqi Li. 2025. Multi‑objective parameter optimization for axial‑radial integrated electromagnetic levitation transport device. Journal of Power Electronics, 25, 11, (2025), 2041-2050. DOI: 10.1007/s43236-025-01034-0.