2019 IEEE Energy Conversion Congress and Exposition (ECCE) 2019
DOI: 10.1109/ecce.2019.8912205
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Very-High-Speed Miniaturized Permanent Magnet Motors: Design and Optimization

Abstract: This paper aims to present an optimization method for very-high-speed electrical machines based on multiphysical analytical models. Analytical models allow a fast design but have to be robust and reliable. The set of models presented is very complete and covers the mechanical design of the rotor, the computation of the losses and the computation of the back EMF and torque constants. All the models have been validated on a 400 krpm prototype, which is, to the authors' knowledge, one of the smallest and fastest … Show more

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Cited by 4 publications
(5 citation statements)
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References 25 publications
(35 reference statements)
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“…Electronics 2022, 11, 1024 2 of 16 the motor and battery greatly affect the size and weight of the product, technical measures to minimize the motor size and battery weight are required [4][5][6][7]. This paper proposes a control and efficient operation plan with a system that can drive a product by applying both ac power and dc battery power sources.…”
Section: System Descriptionmentioning
confidence: 99%
See 2 more Smart Citations
“…Electronics 2022, 11, 1024 2 of 16 the motor and battery greatly affect the size and weight of the product, technical measures to minimize the motor size and battery weight are required [4][5][6][7]. This paper proposes a control and efficient operation plan with a system that can drive a product by applying both ac power and dc battery power sources.…”
Section: System Descriptionmentioning
confidence: 99%
“…The load resistance is R and the average output power is P O , the average value of the output current is I O without considering the converter efficiency. P O can be expressed as Equation (6) from Equation (5).…”
Section: Boostmentioning
confidence: 99%
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“…where By is the peak magnetic flux density in the stator yoke [11], L PM is the axial length of the PM (assumed to be shorter than the axial length of the stator), k f is the stacking factor and c Iron1 and c Iron2 are coefficients obtained by regression. This model is also used in [7] for a bearingless motor.…”
Section: Iron Lossesmentioning
confidence: 99%
“…Finally, an experimental method to isolate every losses component due to the rotation of the rotor is proposed and tested on the prototype in Section IV. This allows to validate the proposed models and to include them in an optimization process to further obtain a new design with lower losses [11]. The losses components due to the rotation are:…”
Section: Introductionmentioning
confidence: 99%