Parasitic loads in torque standard machines : a characterisation, comparison, and evaluation
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource
- Language
-
Englisch
- Bibliographic citation
-
In: Acta IMEKO 8(3), Seiten/Artikel-Nr.:78-89, 10.21014/acta_imeko.v8i3.607
- Event
-
Veröffentlichung
- (where)
-
Aachen
- (who)
-
Universitätsbibliothek der RWTH Aachen
- (when)
-
2019
- Creator
-
Baumgarten, Sebastian
Röske, Dirk
Hiiro, Jussi Ala
Vavrečka, Lukáš
Kock, Stefan
Gnauert, Jonas
- DOI
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10.18154/RWTH-2020-02067
- URN
-
urn:nbn:de:101:1-2021032314524952348912
- Rights
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:28 AM CEST
Data provider
This object is provided by:
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Associated
- Baumgarten, Sebastian
- Röske, Dirk
- Hiiro, Jussi Ala
- Vavrečka, Lukáš
- Kock, Stefan
- Gnauert, Jonas
- Universitätsbibliothek der RWTH Aachen
Time of origin
- 2019
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Direct instantaneous torque control for switched reluctance machines considering mutual coupling
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Modeling and optimal torque control of saturated surface-mounted permanent magnet synchronous machines
Novel approaches to reduce the uncertainty of torque standard machines for small torques
Machine learning for computationally efficient electrical loads estimation in consumer washing machines
High-precision torque control of inverter-fed induction machines with instantaneous phase voltage sensing
Simulation Method for the Characterisation of the Torque Transducers in MN·m range
Torque Control for Mobile Machines
Position sensorless torque control of switched reluctance machines
Parasitic load components for torque and force calibration: a Digital Twin concept
Test method for torque transmissibility in high-speed electric machines
Predictive PWM-based direct instantaneous torque control for switched reluctance machines
Direct instantaneous torque control for switched reluctance machines considering mutual coupling
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Modeling and optimal torque control of saturated surface-mounted permanent magnet synchronous machines
Novel approaches to reduce the uncertainty of torque standard machines for small torques
Machine learning for computationally efficient electrical loads estimation in consumer washing machines
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