C
Chris Gerada
Researcher at University of Nottingham
Publications - 634
Citations - 10494
Chris Gerada is an academic researcher from University of Nottingham. The author has contributed to research in topics: Rotor (electric) & Stator. The author has an hindex of 37, co-authored 555 publications receiving 7161 citations. Previous affiliations of Chris Gerada include The University of Nottingham Ningbo China & Beihang University.
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High-Speed Permanent Magnet Synchronous Motor Iron Loss Calculation Method Considering Multiphysics Factors
TL;DR: In this paper, the authors proposed different iron loss models for high speed permanent magnet synchronous motors (HSPMSMs) considering the interaction effect of the multiphysics factors, including high frequency, temperature, and compressive stress.
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A High-Speed Permanent-Magnet Machine for Fault-Tolerant Drivetrains
TL;DR: A multidisciplinary approach to the optimal design of the machine is adopted, targeted at minimizing the additional losses resulting from faulty operating conditions and accounting for the remedial control strategy implemented.
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Model Predictive Control for a Dual-Active Bridge Inverter With a Floating Bridge
TL;DR: The proposed floating bridge topology eliminates the need for isolation transformer in a dual inverter system and therefore reduces the size, weight, and losses in the system.
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Considerations on the Development of an Electric Drive for a Secondary Flight Control Electromechanical Actuator
Paolo Giangrande,Alessandro Galassini,Savvas Papadopoulos,A. Al-Timimy,Giovanni Lo Calzo,Michele Degano,Michael Galea,Chris Gerada +7 more
TL;DR: A linear-geared electromechanical actuator for secondary flight control systems, where the safety and availability requirements are fulfilled by replicating the electric drive acting on the drivetrain.
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An Accurate Wide-Speed Range Control Method of IPMSM Considering Resistive Voltage Drop and Magnetic Saturation
TL;DR: Newton–Raphson algorithm for improving the control accuracy of the current set-points is proposed and is able to converge to accurate solutions in few numbers of iterations with reduced execution time, which can be easily implemented on an off-the-shelf digital signal processor.