High-Precision Modeling of UAV Electric Propulsion for Improving Endurance Estimation

The electric propulsion system is a critical determinant of unmanned aerial vehicles’ (UAVs’) operational capabilities, particularly endurance performance. This paper proposes a high-precision modeling framework for UAV electric propulsion systems to improve endurance estimation. By integrating dimensional analysis based on the Buckingham $\pi$ theorem with data-driven parameter fitting, the method accurately predicts propeller thrust, power, and motor current under varying inflow conditions using limited experimental data. The proposed models and complete implementation are publicly available, facilitating reproducibility and further research. The key novelty of this work lies in the tight integration of dimensional analysis (via Buckingham’s $\pi$ theorem) with a data-driven torque-based motor current model, enabling accurate cross-configuration predictions for both propeller aerodynamics and motor electrical characteristics using limited experimental data. The model is rigorously validated against the UIUC propeller database, a custom-built inflow test rig, and actual flight tests. The results demonstrate that the proposed approach achieves superior prediction accuracy across multiple propeller-motor configurations while significantly reducing computational costs. This work provides a reliable foundation for improving UAV endurance estimation and propulsion system design.