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Ian P. Brown
Researcher at Illinois Institute of Technology
Publications - 55
Citations - 1037
Ian P. Brown is an academic researcher from Illinois Institute of Technology. The author has contributed to research in topics: Rotor (electric) & Synchronous motor. The author has an hindex of 12, co-authored 50 publications receiving 638 citations. Previous affiliations of Ian P. Brown include University of Wisconsin-Madison & A. O. Smith Water Products Company.
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Comparative Study of Interior Permanent Magnet, Induction, and Switched Reluctance Motor Drives for EV and HEV Applications
TL;DR: In this paper, the design and comparative evaluation for an interior permanent magnet synchronous motor (IPMSM) with distributed winding and concentrated winding, induction motor (IM), and switched reluctance motor (SRM) for an electric vehicle or hybrid electric vehicle (HEV) application is presented.
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Design and Demonstration of a Wound Field Synchronous Machine for Electric Vehicle Traction With Brushless Capacitive Field Excitation
Antonio Di Gioia,Ian P. Brown,Yue Nie,Ryan Knippel,Daniel C. Ludois,Jiejian Dai,Skyler Hagen,Christian Alteheld +7 more
TL;DR: In this article, a high power density wound field synchronous machine (WFSM) was designed for brushless rotor field excitation using an axial flux hydrodynamic capacitive power coupler (CPC).
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Synchronous Generator Brushless Field Excitation and Voltage Regulation via Capacitive Coupling Through Journal Bearings
TL;DR: A brushless excitation approach using ceramic insulated sleeve (journal) bearings with oil lubrication to form capacitively coupled slip rings, in contrast to more traditional inductive brushless exiters and rotary transformers, is presented in this article.
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Simultaneous Magnetic and Structural Topology Optimization of Synchronous Reluctance Machine Rotors
Feng Guo,Ian P. Brown +1 more
TL;DR: In this paper, the simultaneous magnetic and structural topology optimization of a transverse laminated synchronous reluctance machine rotor using a solid isotropic with material penalization (SIMP)-based approach with the globally convergent method of moving asymptotes (GCMMA) optimization algorithm is presented.
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Framework and Solution Techniques for Suppressing Electric Machine Winding MMF Space Harmonics by Varying Slot Distribution and Coil Turns
Nanjun Tang,Ian P. Brown +1 more
TL;DR: In this article, closed-form expressions for the winding factor and harmonic magnitude established from a mathematical representation of winding functions are used to formulate the MMF space harmonic suppression problem. But the results of this paper are limited to the case of fractional-slot concentrated windings.