Work

Dynamic programming-based energy optimization for the series hybrid electric fixed-wing VTOL UAV

Year: 2025

Type: article

Abstract: Hybrid electric fixed-wing vertical take-off and landing (VTOL) UAVs are increasingly utilized for reconnaissance, patrol, and cargo transportation due to their VTOL capability and efficient cruise performance. Enhancing energy efficiency is essential for further advancing this type of aircraft. However, current research on hybrid-electric energy management primarily focuses on conventional aircraft or employs simplified optimization processes using basic rule strategies. The unique energy requirements and power system architecture of hybrid-electric fixed-wing VTOL UAVs result in energy management processes that differ significantly from those of traditional fixed-wing or rotary-wing UAVs. Research on suitable energy management strategies for this platform remains insufficient. To address this gap, a dynamic programming-based energy management strategy for hybrid electric fixed-wing VTOL UAVs is proposed in this paper. Three core models, a hybrid power system model, a fixed-wing VTOL UAV power demand model, and a hybrid energy management model oriented to the mission profile, are established. The application effects of the proposed dynamic programming strategy are compared with those of two state machine control models: basic rule and engine ON-OFF rule. This work is intended to provide a reference for the application of energy management strategy aimed at enhancing fuel economy and reducing operational costs during mission execution for hybrid electric fixed-wing VTOL UAVs.

Source: Energy Reports

DOI: 10.1016/j.egyr.2025.11.114

Authors: Cheng He, Yuqi Tong, Guanxiong Li, Shipeng Yang, Diyi Liu

Institutions: Nanjing University of Aeronautics and Astronautics, Shanghai Academy of Spaceflight Technology, Sichuan University, China Aerodynamics Research and Development Center, State Key Laboratory of Aerodynamics

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: $3,040