Bibliographische Detailangaben
| Titel: |
ENHANCING PERFORMANCE AND EFFICIENCY OF DCDC BOOST CONVERTER USING GOLDEN EAGLE OPTIMIZATION. |
| Autoren: |
Jallad, Jafar, Badran, Ola |
| Quelle: |
Kufa Journal of Engineering; Jan2026, Vol. 17 Issue 1, p330-350, 21p |
| Schlagwörter: |
DC-to-DC converters, OPTIMIZATION algorithms, POWER electronics, RENEWABLE energy sources, PID controllers, SIMULATION software |
| Abstract (English): |
Despite DC-DC converters are currently extensively utilized within power electronics for their effectiveness in generating a stable DC output with high efficiency, the fact that they are inherently nonlinear makes the selection of advanced converter components and control techniques indispensable for their improvement. In the context of overcoming the performance constraints of DC-DC boost converters, the purpose of the current research work is to use the concept of optimization, which targets the critical parameters of the continuous conduction mode. During the optimization procedure, the objective is to identify the best possible parameters for the inductor, the capacitor, as well as the frequency of switching. In addition to that, the adjustment of the parameters of the Proportional-Integral (PI) controller is carried out to improve the performance characteristics of the DC-DC boost converter circuit. The use of the Golden Eagle Optimization algorithm functions as the basis of the presented optimization approach. The validity of the current technique using the Golden Eagle Optimization algorithm for the design of the DC-DC boost converter circuit is demonstrated through a MATLAB/Simulink simulation. From the results, it can be seen that the proposed design using GEO outperforms various classical optimal techniques such as Grey Wolf Optimizer, Firefly Algorithm, Simulated Annealing, Particle Swarm Optimization, and Moth Flame Optimization. This proposed design using GEO results in a power loss reduction of over 6% and has 10% improvement in output voltage over the latest techniques proposed by Grey Wolf Optimizer. This again manifests the potential of GEO in developing boost converters in terms of power electronics and renewable energy sources. [ABSTRACT FROM AUTHOR] |
| Abstract (Arabic): |
المقال يركز على تعزيز أداء وكفاءة محولات DC-DC من نوع البوست من خلال تطبيق خوارزمية تحسين النسر الذهبي (GEO). تتناول الدراسة الخصائص غير الخطية المتأصلة في محولات DC-DC، مع التأكيد على الحاجة إلى تقنيات تحسين متقدمة لتحسين اختيار المكونات وطرق التحكم. تُظهر الدراسة أن خوارزمية GEO تقلل بشكل كبير من خسائر الطاقة بأكثر من 6% وتحسن الجهد الناتج بنسبة 10% مقارنةً بأساليب التحسين التقليدية مثل مُحسّن الذئب الرمادي (Grey Wolf Optimizer) وتحسين سرب الجسيمات (Particle Swarm Optimization). تشير النتائج إلى أن GEO هي نهج قوي وفعال لتحسين محولات DC-DC من نوع البوست، مع تطبيقات محتملة في إلكترونيات الطاقة وأنظمة الطاقة المتجددة. [Extracted from the article] |
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Copyright of Kufa Journal of Engineering is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Datenbank: |
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