Work

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

Year: 2025

Type: article

Abstract: 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.

Source: ICT Express

DOI: 10.1016/j.icte.2025.09.014

Authors: Md Shahriar Nazim, Md Minhazur Rahman, Md Ibne Joha, Yeong Min Jang

Institution: Kookmin University

Language: English

Topic: Electric and Hybrid Vehicle Technologies

Subfield: Automotive Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $1,500