Version 1
: Received: 13 July 2024 / Approved: 14 July 2024 / Online: 15 July 2024 (08:07:08 CEST)
How to cite:
Sanchez, J.; Arteaga, J. M.; Zesiger, C.; Mitcheson, P.; Young, D.; Roundy, S. Coil Misalignment Perception and Correction in a Mobile Inductive Power Transfer System for Wirelessly Recharging Underground Agricultural Sensors. Preprints2024, 2024071129. https://doi.org/10.20944/preprints202407.1129.v1
Sanchez, J.; Arteaga, J. M.; Zesiger, C.; Mitcheson, P.; Young, D.; Roundy, S. Coil Misalignment Perception and Correction in a Mobile Inductive Power Transfer System for Wirelessly Recharging Underground Agricultural Sensors. Preprints 2024, 2024071129. https://doi.org/10.20944/preprints202407.1129.v1
Sanchez, J.; Arteaga, J. M.; Zesiger, C.; Mitcheson, P.; Young, D.; Roundy, S. Coil Misalignment Perception and Correction in a Mobile Inductive Power Transfer System for Wirelessly Recharging Underground Agricultural Sensors. Preprints2024, 2024071129. https://doi.org/10.20944/preprints202407.1129.v1
APA Style
Sanchez, J., Arteaga, J. M., Zesiger, C., Mitcheson, P., Young, D., & Roundy, S. (2024). Coil Misalignment Perception and Correction in a Mobile Inductive Power Transfer System for Wirelessly Recharging Underground Agricultural Sensors. Preprints. https://doi.org/10.20944/preprints202407.1129.v1
Chicago/Turabian Style
Sanchez, J., Darrin Young and Shad Roundy. 2024 "Coil Misalignment Perception and Correction in a Mobile Inductive Power Transfer System for Wirelessly Recharging Underground Agricultural Sensors" Preprints. https://doi.org/10.20944/preprints202407.1129.v1
Abstract
Field implementations of inductive power transfer (IPT) face many practical challenges that dramatically reduce power transmission effectiveness. Coil misalignment is a persistent issue in IPT systems, especially in applications involving vehicles or nonvisible coils. Furthermore, magnetic field symmetry convolutes the decomposition of misalignment measurements in multiple dimensions and frequently impedes the efficacy of traditional position correction strategies. This paper presents an automated methodology to sense misalignments and align IPT coils using robotic actuators and sequential Monte Carlo methods. The misalignment of a Class EF inverter-driven IPT system was modeled by tracking changes as its coils move apart laterally and distally. These models were integrated with particle filters to estimate the location of a hidden coil in 3D, given a sequence of sensor measurements. During laboratory tests on a Cartesian robot, these algorithms aligned the IPT system within 1 cm (0.025 coil diameters) of peak lateral alignment. On average, the alignment algorithms required less than four sensor measurements for localization. After laboratory testing, this approach was implemented with an agricultural sensor platform at the Utah Agricultural Experiment Station in Kaysville, Utah. In this implementation, a buried sensor platform was successfully charged using an aboveground, vehicle-mounted transmitter.
Keywords
Agricultural soil sensing; inductive power transfer; Monte Carlo methods; machine learning; power transfer coil misalignment; wireless power transfer; wireless underground sensor networks
Subject
Engineering, Electrical and Electronic Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
