Mohamed S. Elkerdany, Ibrahim M. Safwat, Ahmed Medhat M. Youssef, Mohamed M. Elkhatib
{"title":"An intelligent energy management system for enhanced performance in electric UAVs","authors":"Mohamed S. Elkerdany, Ibrahim M. Safwat, Ahmed Medhat M. Youssef, Mohamed M. Elkhatib","doi":"10.1007/s42401-025-00343-3","DOIUrl":null,"url":null,"abstract":"<div><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></div>","PeriodicalId":36309,"journal":{"name":"Aerospace Systems","volume":"8 3","pages":"701 - 716"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Aerospace Systems","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s42401-025-00343-3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Earth and Planetary Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍:
Aerospace Systems provides an international, peer-reviewed forum which focuses on system-level research and development regarding aeronautics and astronautics. The journal emphasizes the unique role and increasing importance of informatics on aerospace. It fills a gap in current publishing coverage from outer space vehicles to atmospheric vehicles by highlighting interdisciplinary science, technology and engineering.
Potential topics include, but are not limited to:
Trans-space vehicle systems design and integration
Air vehicle systems
Space vehicle systems
Near-space vehicle systems
Aerospace robotics and unmanned system
Communication, navigation and surveillance
Aerodynamics and aircraft design
Dynamics and control
Aerospace propulsion
Avionics system
Opto-electronic system
Air traffic management
Earth observation
Deep space exploration
Bionic micro-aircraft/spacecraft
Intelligent sensing and Information fusion