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Modeling and Analysis of a Linear Generator for High Speed Maglev Train

descriptionPublicationkeyboard_double_arrow_right Article , Journal 01 Jan 2021Publisher:Institute of Electrical and Electronics Engineers (IEEE)Journal:IEEE Access, volume 9, pages 24,637-24,645 (eissn: 2169-3536,

Authors: Sansan Ding; Weitao Han; Jinji Sun; Fujie Jiang; Guimei Deng; Yunqi Shi;

doi: 10.1109/access.2021.3056796

Modeling and Analysis of a Linear Generator for High Speed Maglev Train

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Abstract

This paper investigates a linear generator (LIG) for application in high speed maglev train. Its configuration and working principle are introduced in detail. The mathematic models of magnetic field and induced voltage are established by the equivalent magnetic circuit method and the law of electromagnetic induction respectively, through which the characteristics of LIG and impact factors are analyzed preliminarily. An analytical and numerical method is proposed to analyze the characteristics of LIG further, in which the finite element model is applied to calculate the magnetic field accurately and the analytical model is used for the induced voltage calculation in a discrete way. The relationships of induced voltage amplitude and speed, induced voltage frequency and speed are clarified, providing the basis for the design of power supply system on vehicle. Finally, the experiments for the magnetic field and induced voltage are carried out on the performance test bench of magnet and real vehicle respectively to validate the analysis results.

Related Organizations

Beihua University
China (People's Republic of)
Beihang University
China (People's Republic of)

Keywords

Linear generator, analytical and numerical method, induced voltage, maglev train, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	7
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%