Neuro-fuzzy approaches to estimating thermal overstress behavior of IGBTs

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23220%2F21%3A43962329" target="_blank" >RIV/49777513:23220/21:43962329 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/9432584" target="_blank" >https://ieeexplore.ieee.org/document/9432584</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/PEMC48073.2021.9432584" target="_blank" >10.1109/PEMC48073.2021.9432584</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Neuro-fuzzy approaches to estimating thermal overstress behavior of IGBTs

Popis výsledku v původním jazyce

The Thermal overstress behavior of power semiconductor components is a determining factor to evaluate the reliability and performance of power electronic devices. Many theoretical and empirical methods have been presented to address the thermal effects of power electronics components on the quality of power systems. However, analyzing temperature brings to us a large number of uncertainties and nonlinearities affecting the accuracy of modeling. This paper proposes three neuro-fuzzy based techniques to estimate the temperature of Insulated Gate Bipolar Transistors (IGBTs). These techniques include grid partitioning clustering, Fuzzy C-Means (FCM) clustering, and subtractive clustering. An experimental dataset containing over 1.5 million data points is used to develop and train the proposed neuro-fuzzy approaches. This dataset is obtained during a comprehensive investigation on IGBTs and thermal effects by scientists at Ames Research Center of NASA. Preliminary results have demonstrated that the applied approaches are superior to estimating the thermal overstress behavior of IGBTs.

Název v anglickém jazyce

Neuro-fuzzy approaches to estimating thermal overstress behavior of IGBTs

Popis výsledku anglicky

The Thermal overstress behavior of power semiconductor components is a determining factor to evaluate the reliability and performance of power electronic devices. Many theoretical and empirical methods have been presented to address the thermal effects of power electronics components on the quality of power systems. However, analyzing temperature brings to us a large number of uncertainties and nonlinearities affecting the accuracy of modeling. This paper proposes three neuro-fuzzy based techniques to estimate the temperature of Insulated Gate Bipolar Transistors (IGBTs). These techniques include grid partitioning clustering, Fuzzy C-Means (FCM) clustering, and subtractive clustering. An experimental dataset containing over 1.5 million data points is used to develop and train the proposed neuro-fuzzy approaches. This dataset is obtained during a comprehensive investigation on IGBTs and thermal effects by scientists at Ames Research Center of NASA. Preliminary results have demonstrated that the applied approaches are superior to estimating the thermal overstress behavior of IGBTs.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

<a href="/cs/project/EF18_069%2F0009855" target="_blank" >EF18_069/0009855: Elektrotechnické technologie s vysokým podílem vestavěné inteligence</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název statě ve sborníku

2021 IEEE 19th International Power Electronics and Motion Control Conference (PEMC) : /proceedings/

ISBN

978-1-72815-660-6

ISSN

—

e-ISSN

2473-0165

Počet stran výsledku

8

Strana od-do

843-850

Název nakladatele

IEEE

Místo vydání

Piscaway

Místo konání akce

Gliwice, Poland

Datum konání akce

25. 4. 2021

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000723843000120