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UNIVERSITY OF BUCHAREST
FACULTY OF PHYSICS Guest
2026-06-11 23:58 |
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Conference: Bucharest University Faculty of Physics 2026 Meeting
Section: Physics and Technology of Renewable and Alternative Energy Sources
Title:
Intelligent Energy Management and Power Distribution Architectures for Next‑Generation eVTOL Systems
Authors:
Tiberiu Adrian SALAORU (1), Marius POP (1), Vlad TUDORACHE PROHNITCHI (1,2), Adina Diana DOBRIN (3)
*
Affiliation:
1) INCAS – National Institute for Aerospace Research “Elie Carafoli”, B-dul Iuliu Maniu 220, Bucharest 061126, Romania
2) Reykjavik University, Menntavegur 1, Reykjavik, Iceland
3) Faculty of Physics, University of Bucharest, Str. Atomistilor nr. 405, Magurele, Romania
E-mail
salaoru.tiberiu@incas.ro, pop.marius@incas.ro, vlad.tudorache.prohnitchi@gmail.com, dadinadiana1999@yahoo.com
Keywords:
eVTOL power distribution, photovoltaic systems, neural network algorithm
Abstract:
Electrical energy management and power distribution represent critical challenges in the design and operation of electric Vertical Take-Off and Landing (eVTOL) aircraft. These challenges encompass energy storage, power distribution, and protection systems, all of which must operate efficiently and reliably to ensure safe flight conditions. This work focuses on advanced strategies for optimizing electrical power distribution with the dual objective of enhancing operational safety and maximizing energy efficiency. Conventional eVTOL electrical architectures typically rely on a centralized energy storage system consisting of a single battery supplying power to the main loads, such as electric propulsion motors [1]. In contrast, the approach proposed in this study distributes energy storage across multiple battery units, thereby improving redundancy, reducing energy losses, and enabling safer operation under varying load conditions. Several configurations of electrical power distribution are presented, based on the use of single or multiple interconnected power buses, which link various power sources and loads. The most common bus architectures, namely linear and ring topologies, are analyzed in detail, with particular emphasis on their respective advantages and limitations when implemented as single or multiple bus systems. The connectivity between power sources and loads is dynamically managed using a Neural Network (NN) algorithm, which continuously learns the behavior of individual circuit components by monitoring their operating parameters [2]. This adaptive control allows real-time compensation for variations in component performance and enhances overall system efficiency. To further support energy availability, the system integrates a photovoltaic subsystem capable of supplying additional power, particularly in remote locations where grid access is limited. The energy contribution of the photovoltaic system is also optimized through the same NN-based framework, coordinated by a central electrical energy management algorithm [3]. The combined use of distributed storage, optimized power bus architectures, and intelligent control strategies enables improved performance, increased efficiency, and enhanced operational safety in eVTOL systems.
References:
[1] Al Marzooqi, H., Abdulrahman, M., Alramsi, H., Hassan, A., & Zia, M. F. (2024, December). Powering the future of urban air mobility: Electrical design and systems in evtol vehicles. In 2024 International Conference on Engineering and Emerging Technologies (ICEET) (pp. 1-6). IEEE.
[2] Hochreiter, S., & Schmidhuber, J. (1997). Long short-term memory. Neural Computation, 9(8), 1735–1780
[3] M. Pop, M. Tudose, D. Visan, M. Bocioaga, M. Botan, C. Banu, T. Salaoru, A Machine Learning-DrivenWireless System for Structural Health Monitoring, INCAS BULLETIN, (print) ISSN 2066–8201, (online)ISSN 2247–4528, ISSN–L 2066–8201, vol 16, pp 77-93.
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