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Dergiler / Journal of Artificial Intelligence and Data Science / 2024 / Cilt: 4 Sayı: 2

Optimization of Thermal Management for Cooling System of Power Electronics Modules Consisting Insulated-Gate Bipolar Transistor Using Neuro-Regression Analysis and Non-Traditional Algorithms

Melih Savran(İZMİR KATİP ÇELEBİ ÜNİVERSİTESİ)0000-0001-8343-1073
Ece Nur Yüncü(İZMİR KATİP ÇELEBİ ÜNİVERSİTESİ)0009-0002-3195-124X
Levent Aydın(İZMİR KATİP ÇELEBİ ÜNİVERSİTESİ)0000-0003-0483-0071
Sayfa
68–78
Yayın Tarihi
2024-12-27
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

The results indicate a 12 % reduction in the minimum IGBT temperature.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Thermal management and extreme temperatures critically influence the performance of power electronics systems, especially those utilizing IGBT (Insulated-Gate Bipolar Transistor) and diode components.
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Temel Bulgular & Veri:To achieve temperature minimization, optimum values of design variables: coolant flow rate (L/min), distance from the vortex generator (mm), height (μmm), and width of the first pin-fin (μmm), and distance of the vortex generator from the surface (μmm) were determined.
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Sonuç & Katkı:The results indicate a 12 % reduction in the minimum IGBT temperature.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:neuro-regression analysis · thermal management · Insulated-Gate Bipolar Transistor

Abstract

Thermal management and extreme temperatures critically influence the performance of power electronics systems, especially those utilizing IGBT (Insulated-Gate Bipolar Transistor) and diode components. Various parameters govern the cooling efficiency of these systems. In this study, the IGBT temperature was selected as the objective function. To achieve temperature minimization, optimum values of design variables: coolant flow rate (L/min), distance from the vortex generator (mm), height (μmm), and width of the first pin-fin (μmm), and distance of the vortex generator from the surface (μmm) were determined. The mathematical modeling process employed Neuro-Regression analysis. The prediction performance of proposed 14 different regression models were evaluated using R2Training, R2Testing, R2Validation indexes and boundedness check criteria. The Differential Evolution, Nelder Mead, Simulated Annealing, and Random Search algorithms were applied to minimize IGBT temperature. The FOLN (First Order Logarithmic Nonlineer) model emerged as the most successful, achieving a minimum temperature lower than the experimental dataset given in literature. The results indicate a 12 % reduction in the minimum IGBT temperature.

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Bu Makaleye Atıf Yap

Savran, M., Yüncü, E. N., Aydın, L. (2024). Optimization of Thermal Management for Cooling System of Power Electronics Modules Consisting Insulated-Gate Bipolar Transistor Using Neuro-Regression Analysis and Non-Traditional Algorithms. Journal of Artificial Intelligence and Data Science, Cilt: 4 Sayı: 2, 68–78. https://ajindex.com/articles/1618305

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