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Journals / Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi / 2026 / Cilt: 41 Sayı: 1

Optimal Energy Management Using Particle Swarm Optimization for Long Endurance Low Altitude (LALE) UAVs with Continuous Flight Capability

Sürekli uçuş kabiliyetine sahip uzun süre havada kalabilen alçak irtifa (LALE) İHA’lar için parçacık sürü optimizasyonu (PSO) ile optimum enerji yönetimi

Emin Tugay Kekeç(KAPADOKYA ÜNİVERSİTESİ, KAPADOKYA MESLEK YÜKSEKOKULU)0000-0003-1530-996X
Mehmet Konar(ERCİYES ÜNİVERSİTESİ)0000-0002-9317-1196
Pages
29–46
Publication Date
2026-02-19
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The results show that the required power was reduced to 62.47 W, the total electrical energy was optimized to approximately 8.46 MJ, and a balance between the battery and solar panel was achieved, making continuous flight feasible.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, the Particle Swarm Optimization (PSO) algorithm was applied to optimize the design parameters of a solar-powered Low Altitude Long Endurance (LALE) class unmanned aerial vehicle (UAV).
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Key Findings & Data:The main objective is to extend the flight duration beyond 24 hours while minimizing energy consumption and ensuring the system's energy balance conditions.
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Conclusion & Impact:The results show that the required power was reduced to 62.47 W, the total electrical energy was optimized to approximately 8.46 MJ, and a balance between the battery and solar panel was achieved, making continuous flight feasible.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Güneş enerjili İHA · solar İHA optimizasyon · batarya enerji yoğunluğu

Abstract

In this study, the Particle Swarm Optimization (PSO) algorithm was applied to optimize the design parameters of a solar-powered Low Altitude Long Endurance (LALE) class unmanned aerial vehicle (UAV). The main objective is to extend the flight duration beyond 24 hours while minimizing energy consumption and ensuring the system's energy balance conditions. Throughout the optimization process, variables such as wingspan, flight speed, mass, and battery capacity were evaluated, and outputs including required power, total electrical power, and energy demand were calculated. Considering Kayseri, a region in Türkiye with limited annual solar irradiance, the energy production capacity was modeled within realistic constraints. The PSO algorithm employed a penalty function under energy deficiency conditions to maintain solution validity. The results show that the required power was reduced to 62.47 W, the total electrical energy was optimized to approximately 8.46 MJ, and a balance between the battery and solar panel was achieved, making continuous flight feasible. This approach presents an efficient and applicable optimization method, particularly for the design of LALE-class solar-powered UAVs.

Özet

Bu çalışmada, güneş enerjisiyle çalışan alçak irtifa uzun süreli uçuş kabiliyetine sahip (LALE) sınıfı insansız hava aracı (İHA) tasarımı için gerekli tasarım parametrelerinin optimizasyonu hedefiyle Parçacık Sürü Optimizasyonu (PSO) algoritması uygulanmıştır. Hedef, uçuş süresini 24 saatin üzerine çıkarırken enerji tüketimini minimize etmek ve sistemin enerji dengesi şartlarını sağlamaktır. Optimizasyon boyunca kanat açıklığı, uçuş hızı, kütle ve batarya kapasitesi gibi değişkenler değerlendirilmiş; gerekli güç, toplam elektriksel güç ve enerji ihtiyacı gibi çıktılar hesaplanmıştır. Türkiye’de yer alan ve yıllık güneşlenme süresi bakımından sınırlı bir bölge olan Kayseri şehri dikkate alınarak, enerji üretim kapasitesi gerçekçi sınırlar içerisinde modellenmiştir. PSO algoritması, çözüm geçerliliğini sağlamak için enerji yetersizliği koşullarında ceza fonksiyonu uygulamıştır. Elde edilen sonuçlar, gerekli gücün 62,47 W seviyelerine indirildiğini, toplam elektrik enerjisinin yaklaşık 8,46 MJ olarak optimize edildiğini ve batarya ile güneş paneli dengesinin sağlanarak sürekli uçuşun mümkün olduğunu göstermektedir. Bu yöntem, özellikle LALE sınıfı güneş enerjili İHA tasarımlarında verimli ve uygulanabilir bir optimizasyon yaklaşımı sunmaktadır.

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Cite This Article

Kekeç, E. T., Konar, M. (2026). Optimal Energy Management Using Particle Swarm Optimization for Long Endurance Low Altitude (LALE) UAVs with Continuous Flight Capability. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, Cilt: 41 Sayı: 1, 29–46. https://doi.org/10.17341/gazimmfd.1675074

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