A Dead-Time Compensation Strategy Based on an Online Learned Artificial Neural Network

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26620%2F26%3A0197508" target="_blank" >RIV/00216305:26620/26:0197508 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/10948334" target="_blank" >https://ieeexplore.ieee.org/document/10948334</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TIE.2025.3544207" target="_blank" >10.1109/TIE.2025.3544207</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A Dead-Time Compensation Strategy Based on an Online Learned Artificial Neural Network

Popis výsledku v původním jazyce

This article presents an innovative approach to mitigate the harmonic distortion of the phase currents of a permanent magnet synchronous motor (PMSM) controlled by a field-oriented control (FOC) algorithm. The issue of phase current harmonic distortion is often a consequence of the output voltage deformation caused by the non-linearities of the voltage source inverter (VSI). The relationship between the disturbance voltages of the inverter and the phase currents of the motor is non-linear. Therefore, we used an artificial neural network (ANN) to identify the compensation voltages. The topology is designed to allow the neural network to solve complex problems with the limited computing resources available on the AURIX TC397 microcontroller. The input vector is assembled from quantities available in the PMSM FOC algorithm. The online learning process based on the back-propagation algorithm is adapted to operate directly on the microcontroller. The proposed strategy with ANN is verified on a real PMSM. The results show the excellent ability of the proposed ANN to suppress the harmonic distortion of the PMSM phase currents without knowledge of the VSI parameters.

Název v anglickém jazyce

A Dead-Time Compensation Strategy Based on an Online Learned Artificial Neural Network

Popis výsledku anglicky

This article presents an innovative approach to mitigate the harmonic distortion of the phase currents of a permanent magnet synchronous motor (PMSM) controlled by a field-oriented control (FOC) algorithm. The issue of phase current harmonic distortion is often a consequence of the output voltage deformation caused by the non-linearities of the voltage source inverter (VSI). The relationship between the disturbance voltages of the inverter and the phase currents of the motor is non-linear. Therefore, we used an artificial neural network (ANN) to identify the compensation voltages. The topology is designed to allow the neural network to solve complex problems with the limited computing resources available on the AURIX TC397 microcontroller. The input vector is assembled from quantities available in the PMSM FOC algorithm. The online learning process based on the back-propagation algorithm is adapted to operate directly on the microcontroller. The proposed strategy with ANN is verified on a real PMSM. The results show the excellent ability of the proposed ANN to suppress the harmonic distortion of the PMSM phase currents without knowledge of the VSI parameters.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

20205 - Automation and control systems

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

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

Rok uplatnění

2025

Kód důvěrnosti údajů

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

Název periodika

IEEE Transactions on Industrial Electronics

ISSN

0278-0046

e-ISSN

1557-9948

Svazek periodika

72

Číslo periodika v rámci svazku

10

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

11

Strana od-do

10574-10584

Kód UT WoS článku

001470945300001

EID výsledku v databázi Scopus

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