Abstract

Outer-rotor switched reluctance machines (SRMs) have drawn much attention as promising candidates for in-wheel direct-drive motors of future electric vehicles. This article presents a systematic performance comparison of three outer-rotor SRM topologies for in-wheel traction applications in terms of the specific torque, electromagnetic efficiency, torque ripple, radial force, and mechanical aspects. A generalized design optimization framework for SRMs is proposed to enable the fast evaluation of large numbers of designs generated from the differential evolution by incorporating an analytical current profile estimation into the transient finite element analysis. The relationship between the saliency ratio and converter volt-ampere rating is also discussed. The calculations are then benchmarked with the experimental results from an existing prototype. The effectiveness of the performance prediction method and the proposed optimization approach is validated.

Document Type

Article

Publication Date

1-2021

Notes/Citation Information

Published in IEEE Transactions on Industry Applications, v. 57, issue 1.

© 2020 IEEE Copyright Notice. “Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”

The document available for download is the authors’ manuscript version. The final published version is copyrighted by IEEE and is available as: V. Rallabandi, P. Han, J. Wu, A.M. Cramer, D.M. Ionel, and P. Zhou, “Design Optimization and Comparison of Direct-drive Outer-rotor SRMs Based on Fast Current Profile Estimation and Transient FEA,” in IEEE Transactions on Industry Applications, doi: 10.1109/TIA.2020.3029995

Digital Object Identifier (DOI)

https://doi.org/10.1109/TIA.2020.3029995

Funding Information

The support of ANSYS Inc. and University of Kentucky, the L. Stanley Pigman endowment and the SPARK program, is gratefully acknowledged.

Share

COinS