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Nicolas Bernard

Researcher at University of Nantes

Publications -  50
Citations -  466

Nicolas Bernard is an academic researcher from University of Nantes. The author has contributed to research in topics: Torque & Flywheel. The author has an hindex of 10, co-authored 47 publications receiving 388 citations. Previous affiliations of Nicolas Bernard include École normale supérieure de Cachan.

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Design Optimization with Flux Weakening of High-Speed PMSM for Electrical Vehicle Considering the Driving Cycle

TL;DR: In this paper, the design optimization of a nonsalient high-speed permanent magnet synchronous machine (PMSM) for electric vehicle applications is presented and it will be shown how a deterministic solution to solve the sizing of the machine from a given driving cycle is possible.
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Design Methodology for High-Speed Permanent Magnet Synchronous Machines

TL;DR: In this article, a design methodology for surface permanent magnet synchronous machines, with special application to the case of high-speed machines, is presented, followed by a discussion of the principle and assumptions inherent in the methodology, the analytical model used in the study will be presented.
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Improved Analytical Determination of Eddy Current Losses in Surface Mounted Permanent Magnets of Synchronous Machine

TL;DR: In this paper, an analytical method based on the magnetodynamic problem of a conductive ring is introduced and the obtained results are compared with the ones given by 3-D FEM analysis.
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Design Methodology of a Permanent Magnet Synchronous Machine for a Screwdriver Application

TL;DR: In this article, a permanent magnet synchronous machine associated with a gearbox for a screwdriver application was designed based on a purely analytical formulation, and the optimization of the pole pair number and the choice of the gear ratio was discussed.
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A Novel Methodology for Optimal Design of Fractional Slot With Concentrated Windings

TL;DR: In this paper, a method for optimal design of fractional slot with concentrated windings was developed, based on a generalized analytical model of the winding magnetomotive force combined with a multiobjective genetic algorithm, which searches the optimal winding parameters that maximize the winding factor and minimize the MMF harmonic content.