Optimizing energy efficiency in hybrid UAVs using DQN-based energy management system

With the growing demand for hybrid UAVs, efficient energy management systems (EMS) are becoming increasingly essential. This study proposes a Deep Q-network-based EMS for hybrid UAVs powered by an internal combustion engine and a battery. The EMS optimizes engine efficiency by maintaining operation within its most effective range while the battery supplies additional power as needed. Simulations under dynamically changing conditions demonstrate that the EMS efficiently distributes energy between sources, ensuring reliable power delivery and significantly improving overall efficiency. The proposed system presents a promising approach to enhancing the performance of hybrid UAVs.