Thermal management and fin characteristic optimization of an electronic power supply utilizing Taguchi and ANOVA methods

Husnu Bademlioglu A., Bedrettin Karatas O., Furkan Sokmen K., Yuruklu E.

Applied Thermal Engineering, cilt.252, 2024 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 252
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1016/j.applthermaleng.2024.123671
  • Dergi Adı: Applied Thermal Engineering
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, PASCAL, Aerospace Database, Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, INSPEC, Metadex, DIALNET, Civil Engineering Abstracts
  • Anahtar Kelimeler: ANOVA, CFD, Electronics Cooling, Fin Optimization, Heat Transfer, Taguchi
  • Bursa Uludağ Üniversitesi Adresli: Evet

Özet

In the rapidly advancing field of electronic power supplies, managing thermal performance is critical. This study focuses on optimizing fin geometries to enhance the thermal management of an amplifier used in car multimedia systems, utilizing Taguchi and ANOVA methods for both thermal and volumetric efficiencies. Analyses were conducted on the impact of five distinct fin parameters—fin gap, fin thickness, separated plate thickness, fin base thickness, and fin height—on the system's thermal behavior and the fin volume. Computational Fluid Dynamics (CFD) analyses were performed for 24 different configurations. These analyses showed significant potential for improvement in the original design, with optimizations leading to an 8.31% reduction in the amplifier temperature and a 51.91% reduction in the fin volume. The study identifies fin height as the most effective parameter on the amplifier temperature, with an effect rate of 57.26%, while fin base thickness showed the most significant effect on the fin volume, with an effect rate of 66.98%. These findings not only provide a basis for more efficient design but also offer predictive insights through formulated regression equations, thus reducing the dependency on extensive experimental setups.