Reliable and efficient electric motor and inverter solutions are essential for a variety of applications. Validated digital twin, based on a co-simulation of all drive components, can contribute to these development goals at an early stage of development. Especially for modern SiC-based drive systems, these tools help to analyze the impact of fast-switching inverters and their higher switching frequencies. Within this paper, the development, the experimental validation and the use of a digital twin for an automotive traction drive system is described. The digital twin combines a FEM -based electric machine model with a SiC-inverter circuit simulation. The analyzed drive system consists of an interior permanent magnet synchronous machine (IPMSM) with 175 kW and an 800 V SiC-based inverter. It is shown that the described co-simulation tool leads to more accurate efficiency and overall machine behavior predictions.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Digital Twin for Intelligent and SiC-based Drive Systems


    Beteiligte:
    Liu, Xinjun (Autor:in) / Hofmann, Maximilian (Autor:in) / Streit, Fabian (Autor:in) / Maerz, Martin (Autor:in)


    Erscheinungsdatum :

    2021-12-07


    Format / Umfang :

    2104101 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    An Intelligent Edge-based Digital Twin for Robotics

    Girletti, Luigi / Groshev, Milan / Magalhaes Guimaraes, Carlos Eduardo et al. | BASE | 2020

    Freier Zugriff

    INTELLIGENT DAM MANAGEMENT SYSTEM BASED ON DIGITAL TWIN

    Europäisches Patentamt | 2022

    Freier Zugriff

    INTELLIGENT DAM MANAGEMENT SYSTEM BASED ON DIGITAL TWIN

    LEE YONG | Europäisches Patentamt | 2021

    Freier Zugriff

    Toward intelligent cyber-physical systems: Digital twin meets artificial intelligence

    Groshev, Milan / Magalhaes Guimaraes, Carlos Eduardo / Martín Pérez, Jorge et al. | BASE | 2021

    Freier Zugriff

    Review of Digital twin for intelligent transportation system

    Bao, Lixia / Wang, Qiulan / Jiang, Yan | IEEE | 2021