Optimal Energy Trajectory Generation Based on Pitch-Dependent Mutual Inductance Model for In-Flight Inductive Power Transfer of Drones
- Resource Type
- Conference
- Authors
- Fujimoto, Kota; Fujimoto, Hiroshi; Victorino, Alessandro Correa; Castillo, Pedro
- Source
- 2024 IEEE 18th International Conference on Advanced Motion Control (AMC) Advanced Motion Control (AMC), 2024 IEEE 18th International Conference on. :1-6 Feb, 2024
- Subject
- Aerospace
Communication, Networking and Broadcast Technologies
Photonics and Electrooptics
Robotics and Control Systems
Signal Processing and Analysis
Coils
Inductance
Analytical models
Motors
Trajectory
Transient analysis
Motion control
trajectory generation
pitch-dependent mutual inductance model
in-flight inductive power transfer
- Language
- ISSN
- 1943-6580
To address the challenge of limited flight duration in drones, research into in-flight inductive power transfer has emerged as a crucial solution. In this regard, optimizing the flight trajectory is vital for maximizing energy reception during a single pass over the transfer coils. This paper proposes a strategy that incorporates trajectories optimized on the basis of pitch angle. The optimal trajectories are derived analytically using a pitch-dependent mutual inductance model, and implemented on the drone's motion controller as the reference input for each cascaded control loop. The proposed method has been validated through simulations and experiments. Implementation of two proposed trajectories in the experiments reveals that the drone's receiving power can be improved by 13.4 % maximum compared to the conventional method.