Inductive Power Transfer Coil Misalignment Perception and Correction for Wirelessly Recharging Underground Sensors

Area of Science:

• Robotics and Automation
• Wireless Power Transfer
• Sensor Networks

Background:

• Underground sensor networks face power management challenges, requiring frequent battery maintenance or complex infrastructure.
• Wireless inductive power transfer (IPT) is a potential solution, but coil misalignment hinders its effectiveness, especially in obscured environments.

Purpose of the Study:

• To develop an automated methodology for sensing and correcting misalignment in IPT coils for underground sensor networks.
• To integrate a self-aligning wireless power delivery system with agricultural sensor platforms.

Main Methods:

• Modeling IPT coil misalignment using changes in lateral and distal positions.
• Employing sequential Monte Carlo methods (particle filters) to estimate hidden coil location from sensor measurements.
• Utilizing robotic actuators for automated coil alignment.

Main Results:

• Achieved alignment within 1 cm of peak lateral position in laboratory tests.
• Required an average of fewer than four sensor measurements for coil localization.
• Successfully demonstrated charging of a buried agricultural sensor platform using a vehicle-mounted transmitter.

Conclusions:

• The presented automated alignment strategy effectively corrects IPT coil misalignment without complex sensor or coil designs.
• This work enables practical implementation of robust wireless power solutions for underground sensor networks, particularly in agriculture.