Comparison and Optimization of a Magnetic Lead Screw Applied in Wave Energy Conversions

Tao Xia*, Junhui Li, Yangfei Zhang, Haitao Yu, Kaiyuan Lu


Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review


In order to improve the power density of the wave power generation system, a magnetic lead screw (MLS) is introduced in this paper as a speed-increasing device in a wave energy converter (WEC), which converts low-speed linear wave motion to high-speed rotational motion. Then, several types of MLSs with different topologies, which were optimized, are described. Finite element analysis (FEA) was used to investigate and evaluate their electromagnetic performances, such as the thrust force, torque, air gap magnetic density, etc. The optimized MLS prototype was manufactured, and the measurements verify the FEA results. Finally, a magnetic lead screw hybrid generator (MLSHG) for application to the WEC is proposed. This MLS significantly improved the power density under different wave conditions. When the moving speed v = 0.15 m/s, the output power of the MLSHG and outer-PM linear tubular generator were 923 W and 87 W, respectively, when the load resistance was 5 Ω. The output power of the MLSHG was more than 10 times compared to that of the outer-PM linear tubular generator in a fair comparison. Here, it is shown that the power density and output power of were MLSHG increased greatly.

TidsskriftElectronics (Switzerland)
Udgave nummer18
StatusUdgivet - sep. 2022

Bibliografisk note

Funding Information:
This research was funded by the National Natural Science Foundation of China under grants 41576096 and 41876096, the Youth Fund of Jiangsu Natural Science Foundation under BK20201034, the Jiangsu Distribution Network Intelligent Technology and Equipment Collaborative Innovation Center under XTCX202002, the Natural Science Research Project of Jiangsu Higher Education Institutions under the grant 20KJB470028, and the Scientific Research Fund of Nanjing Institute of Technology (YKJ2019115).

Publisher Copyright:
© 2022 by the authors.


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