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Titel: Optimal parameter determination asynchronous traction engine to improve operating performance
Autor(en): Pirmatov, Nurali
Usmonov, Komil
Berdijev, Usan
Nazirkhonov, Tulagan
Berdiyorov, Ulmasbek
Körperschaft: Hochschule Anhalt
Erscheinungsdatum: 2023
Sprache: Englisch
Schlagwörter: Electric Locomotive
Asynchronous Traction Engine
Electric Power
Zusammenfassung: Increasing the energy performance of rolling stock is one of the most relevant railway transport. One of the ways to achieve these tasks is to determine the optimal parameters of the traction drive of the rolling stock, with which you can create computer simulation models. In this article, the optimal parameters of an asynchronous traction motor of an electric rolling stock are determined. Determination of the parameters of the ATM is necessary to create a computer simulation model that allows reproducing electromagnetic processes in a traction electric drive and converters, as well as processing functions of the simulation results obtained that are adequate to the real conditions of use on electric rolling stock of converters with various control algorithms in traction and regenerative braking modes. In the article, the modes of idling, short circuit and rated load are used to determine the parameters of the ATMin relation to the T-shaped replacement circuit using the method of separation of losses in the engine. Losses in traction converters and traction gearboxes are taken into account in accordance with the power developed by the ATM. The results obtained can be used in a computer simulation model designed to reproduce electromagnetic processes in a traction electric drive and converters, when determining the energy characteristics of electric locomotives with asynchronous traction motors.
URI: https://opendata.uni-halle.de//handle/1981185920/114960
http://dx.doi.org/10.25673/113003
http://dx.doi.org/10.25673/113003
Open-Access: Open-Access-Publikation
Nutzungslizenz: (CC BY-SA 4.0) Creative Commons Namensnennung - Weitergabe unter gleichen Bedingungen 4.0 International(CC BY-SA 4.0) Creative Commons Namensnennung - Weitergabe unter gleichen Bedingungen 4.0 International
Enthalten in den Sammlungen:International Conference on Applied Innovations in IT (ICAIIT)

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