Optimal Design of the Bearingless Induction Motor

Jiahao Chen, Yusuke Fujii, Martin Willard Johnson, Ashad Farhan, Eric L. Severson

Research output: Contribution to journalArticlepeer-review

22 Scopus citations


The bearingless version of the induction motor (IM) has unacceptable performance for high speed or significant power applications. This is due to design challenges that are unique to the bearingless IM, including fundamental topology differences, rotor current induced by the suspension field, and a lack of techniques that can rapidly and accurately model the machine. This article presents a complete investigation into the design topology, modeling, and optimization of bearingless IMs to identify high-efficiency, power-dense designs for a high speed industrial compressor system. Key differences in the design of the bearingless IM from that of the classical line-fed IM are explored and an analytic design approach is proposed. A pole-specific rotor and a combined stator winding are used to improve the machine performance. Computationally efficient finite element modeling techniques are proposed and evaluated based on their ability to accurately calculate bearingless IM design performance metrics. An optimization framework is developed around these advancements using the multiobjective evolutionary algorithm based on decomposition. This article exercises this framework to explore the design space of four different slot-pole combination bearingless IMs for a 50 kW, 30 000 r/min compressor. High performance designs are identified that achieve >96% efficiency with a torque density competitive with high performance servo motors that use contact bearings.

Original languageEnglish (US)
Article number9294075
Pages (from-to)1375-1388
Number of pages14
JournalIEEE Transactions on Industry Applications
Issue number2
StatePublished - Mar 1 2021
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 1972-2012 IEEE.


  • Bearingless motor
  • finite element analysis (FEA)
  • induction motor (IM)
  • magnetic suspension
  • optimization


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