EKF Digital Twinning of Induction Motor Drives for the Metaverse

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23220%2F22%3A43966826" target="_blank" >RIV/49777513:23220/22:43966826 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/9983341" target="_blank" >https://ieeexplore.ieee.org/document/9983341</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ME54704.2022.9983341" target="_blank" >10.1109/ME54704.2022.9983341</a>

Jazyk výsledku

angličtina

Název v původním jazyce

EKF Digital Twinning of Induction Motor Drives for the Metaverse

Popis výsledku v původním jazyce

This paper presents a feasible state estimation of speed sensorless rotor field oriented controlled induction motor (IM) drive based on an accurate Extended Kalman Filter (EKF) digital twin model. Digital Twin is one of the attractive trends for the drive industries which provides physical assets over different operating scenarios in a cost-effective platform with no risk. The practical digital twin of the drive system for the Metaverse environment requires precise mathematical model of the motor, EKF algorithm, appropriate state controllers, and voltage source inverter. The quality of the state estimation with EKF strongly depends on input voltages which mainly come from the inverter. Unlike the previous researches which have adopted low precise ideal inverter model, in this study, a high performance EKF observer is employed based on the practical model of the inverter with rigorously considering the dead-time effects and voltage drops of switching devices. Therefore, operation of the EKF observer with digital twin model of the drive system is validated on a 4kW induction motor using simulation results acquired from MATLAB/Simulink software.

Název v anglickém jazyce

EKF Digital Twinning of Induction Motor Drives for the Metaverse

Popis výsledku anglicky

This paper presents a feasible state estimation of speed sensorless rotor field oriented controlled induction motor (IM) drive based on an accurate Extended Kalman Filter (EKF) digital twin model. Digital Twin is one of the attractive trends for the drive industries which provides physical assets over different operating scenarios in a cost-effective platform with no risk. The practical digital twin of the drive system for the Metaverse environment requires precise mathematical model of the motor, EKF algorithm, appropriate state controllers, and voltage source inverter. The quality of the state estimation with EKF strongly depends on input voltages which mainly come from the inverter. Unlike the previous researches which have adopted low precise ideal inverter model, in this study, a high performance EKF observer is employed based on the practical model of the inverter with rigorously considering the dead-time effects and voltage drops of switching devices. Therefore, operation of the EKF observer with digital twin model of the drive system is validated on a 4kW induction motor using simulation results acquired from MATLAB/Simulink software.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

<a href="/cs/project/EF18_053%2F0016927" target="_blank" >EF18_053/0016927: Mobility Západočeské univerzity v Plzni</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 2022 20th International Conference on Mechatronics - Mechatronika, ME 2022

ISBN

978-1-66541-040-3

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

398-403

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

Pilsen, Czech Republic

Datum konání akce

7. 12. 2022

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000947331700057