推进
电力航天器推进
工程类
汽车工程
航空航天工程
计算机科学
激光推进
控制工程
混合动力系统
海洋工程
作者
Aleksander Suti,Gianpietro Di Rito,Giuseppe Mattei
标识
DOI:10.1016/j.ast.2026.112158
摘要
• Retrofitting of ICE-based propulsion systems into hybrid with reduced modifications. • Experimentally validated electro-thermal propulsion model and UAV flight dynamics. • Supervisory Hybrid Control Computer with nonlinear PI-based OOL tracking EMS. • MIL tests demonstrating reduced fuel consumption and ICE lower thermal stress. The inherent advantages of electric propulsion systems in terms of torque density, compactness, efficiency, and maintainability is nowadays driving research and development activities on UAVs towards new configurations. Given the limited energy density and reliability of full-electric solutions, a short-term strategy entails the reconfiguration of conventional platforms based on internal combustion engines into hybrid electric propulsion systems. This approach leverages onboard electric generators installed in long-endurance UAVs, by reconfiguring them as booster motors during high-power phases such as take-off or climb, thus retrofitting existing platforms with minimal changes. This paper supports this concept by demonstrating, through simulation, the feasibility of retrofitting a hybrid electric propulsion system on a lightweight long-endurance UAV. A simulation framework based on lumped-parameter models of the main subsystems, modelling electrical, mechanical and thermal dynamics has been developed and experimentally validated at subsystem-level, and then integrated with the simulator of the longitudinal flight dynamics of a reference UAV. The simulation framework has been then adapted in terms of control and power management stategies for implementing hybrid propulsion capabilities. The hybrid system operation, which is based on tracking the optimum operating line of the combustion engine, has been finally assessed through model-in-the-loop tests. The results demonstrate reduced fuel consumption and lower thermal stress of the internal combustion engine thanks to the adopted energy management strategy.
科研通智能强力驱动
Strongly Powered by AbleSci AI