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<p>Unmanned aerial vehicles (UAVs) propelled by electricity have emerged as a prominent concept in aviation due to their eco-friendly and stealth characteristics. To address the limitations of Polymer Membrane Fuel Cell (PMFC), which serve as the primary power source but exhibit sluggish responses to sudden load changes, this research proposes a novel hybrid power system incorporating a Li-Ion battery. This hybrid setup ensures superior dynamic response while maintaining high power-to-weight efficiency. This paper presents an intelligent energy management system (EMS), which effectively regulates power flow between the PMFC and Li-Ion battery through a multi-input multi-output (MIMO) control framework. The uniqueness of this study lies in the comparative evaluation of two advanced EMS control strategies: Fuzzy Logic Control and the Adaptive Neuro-Fuzzy Inference System (ANFIS), under multiple flight modes. By thoroughly analyzing system transients and dynamic behaviors using MATLAB/SIMULINK, this work provides a detailed insight into optimizing UAV power efficiency. Unlike previous studies, this research highlights the distinct advantages and limitations of each control strategy for different flight phases, providing a comprehensive benchmark for future EMS designs in UAV applications.</p>

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An intelligent energy management system for enhanced performance in electric UAVs

  • 期刊论文

  • 发表日期：

    2025年1月26日

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  • Mohamed S. Elkerdany,
  • Ibrahim M. Safwat,
  • Ahmed Medhat M. Youssef,
  • Mohamed M. Elkhatib

摘要

Unmanned aerial vehicles (UAVs) propelled by electricity have emerged as a prominent concept in aviation due to their eco-friendly and stealth characteristics. To address the limitations of Polymer Membrane Fuel Cell (PMFC), which serve as the primary power source but exhibit sluggish responses to sudden load changes, this research proposes a novel hybrid power system incorporating a Li-Ion battery. This hybrid setup ensures superior dynamic response while maintaining high power-to-weight efficiency. This paper presents an intelligent energy management system (EMS), which effectively regulates power flow between the PMFC and Li-Ion battery through a multi-input multi-output (MIMO) control framework. The uniqueness of this study lies in the comparative evaluation of two advanced EMS control strategies: Fuzzy Logic Control and the Adaptive Neuro-Fuzzy Inference System (ANFIS), under multiple flight modes. By thoroughly analyzing system transients and dynamic behaviors using MATLAB/SIMULINK, this work provides a detailed insight into optimizing UAV power efficiency. Unlike previous studies, this research highlights the distinct advantages and limitations of each control strategy for different flight phases, providing a comprehensive benchmark for future EMS designs in UAV applications.