Modeling and Control of Solar-Assisted UAV Propulsion with Integrated Fuel Cell, Battery, and DAB Power Routing

Abstract This research addresses the need for real-time, physics-informed simulation of hybrid electric propulsion systems in long-endurance unmanned aerial vehicles (UAVs), where tight coupling between energy sources, thermal-electrical dynamics, and propulsion loads creates complex control challenges. We present a unified, low-dimensional nonlinear state-space model that captures the core interactions between solar photovoltaic input, a fuel-cell-assisted lithium-ion battery, a bidirectional dual active bridge (DAB) converter, and a three-phase inverter-driven brushless DC motor. The model incorporates key nonlinearities, including temperature-dependent battery resistance, membrane-hydration-dependent fuel cell losses, maximum power point tracking (MPPT) for solar input, and torque-speed-dependent motor back-EMF. Central to the architecture is the coordination between the fuel cell and battery, where power sharing dynamically adapts to propulsion load, solar availability, and state-of-charge to ensure robust bus voltage regulation without over-reliance on any single source. Designed for real-time execution, the model?s compact form enables closed-loop simulation with external flight dynamics via UDP communication to X-Plane, supporting rapid prototyping, control validation, and hardware-in-the-loop integration. Simulation results demonstrate stable transient response, effective fuel cell ramping under power deficit, and temperature-aware energy management. This framework enables high-fidelity energy system analysis without the computational overhead of full-order multiphysics models, making it well suited for onboard implementation and design trade studies for future hybrid UAV missions.

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Publication Details

Journal
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B Mechanical Engineering
Published
2025-10-11
DOI
https://doi.org/10.1115/1.4070093
Primary Topic
UAV Applications and Optimization
Type
article
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article

Modeling and Control of Solar-Assisted UAV Propulsion with Integrated Fuel Cell, Battery, and DAB Power Routing

Declan Mallamo, D.L. Harmon, Vincent Kolman
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B Mechanical Engineering
UAV Applications and Optimization
article

Modeling and Control of Solar-Assisted UAV Propulsion with Integrated Fuel Cell, Battery, and DAB Power Routing

Declan Mallamo, D.L. Harmon, Vincent Kolman
article en

Abstract

Abstract This research addresses the need for real-time, physics-informed simulation of hybrid electric propulsion systems in long-endurance unmanned aerial vehicles (UAVs), where tight coupling between energy sources, thermal-electrical dynamics, and propulsion loads creates complex control challenges. We present a unified, low-dimensional nonlinear state-space model that captures the core interactions between solar photovoltaic input, a fuel-cell-assisted lithium-ion battery, a bidirectional dual active bridge (DAB) converter, and a three-phase inverter-driven brushless DC motor. The model incorporates key nonlinearities, including temperature-dependent battery resistance, membrane-hydration-dependent fuel cell losses, maximum power point tracking (MPPT) for solar input, and torque-speed-dependent motor back-EMF. Central to the architecture is the coordination between the fuel cell and battery, where power sharing dynamically adapts to propulsion load, solar availability, and state-of-charge to ensure robust bus voltage regulation without over-reliance on any single source. Designed for real-time execution, the model?s compact form enables closed-loop simulation with external flight dynamics via UDP communication to X-Plane, supporting rapid prototyping, control validation, and hardware-in-the-loop integration. Simulation results demonstrate stable transient response, effective fuel cell ramping under power deficit, and temperature-aware energy management. This framework enables high-fidelity energy system analysis without the computational overhead of full-order multiphysics models, making it well suited for onboard implementation and design trade studies for future hybrid UAV missions.

ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B Mechanical Engineering
Naval Air Systems Command (US)
Openalex Percentile: Top 61%
UAV Applications and Optimization
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Modeling and Control of Solar-Assisted UAV Propulsion with Integrated Fuel Cell, Battery, and DAB Power Routing — Declan Mallamo, D.L. Harmon, et al. · ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B Mechanical Engineering (2025) | TGRS Research Map | TGRS