Shad Roundy

This paper presents the design, lab characterization, and field test of two wireless battery-free underground soil moisture sensing systems for future sustainable agricultural application. To overcome the limitations of cable connection and battery maintenance associated with the conventional technologies, we propose a wireless battery-free active sensing system employing a capacitive sensing scheme coupled with an ultra-low-power tunnel diode oscillator to provide frequency modulated data telemetry with a total power dissipation of 0.32mW, and a wireless passive sensing system utilizing a time-domain resonant response-based sensing technique that consumes zero DC power. Both systems are operated wirelessly via inductive coupling to enable the active sensing system and the passive sensing system capable of operating at 30cm and 15cm below the ground surface, respectively. Robust 3D-printed sensor packaging ensures long-term field deployment. Field tests over 40 days demonstrate that the wireless active sensing system achieves an accurate soil moisture measurement with an error less than 3.5% after temperature compensation, while the passive sensing system attains an error less than 1.5%. The proposed systems can provide reliable and low-maintenance solutions for large-scale in-situ soil moisture monitoring, critical for enabling precision irrigation and efficient water resource usage.

Radial (also known as radial-flux) magnetic torque couplers (MTCs) enable the transfer of torque between an inner rotor (IR) and an outer rotor (OR), each equipped with a set of permanent magnets. In a previous article, we used dimensional analysis to find the minimum set of nondimensional parameters required to characterize an MTC, and then performed a parametric optimization to maximize the synchronous torque (i.e., the torque required to cog the IR with respect to the OR) in a given package size. However, we only explicitly optimized an MTC with 16 IR magnets and 16 OR magnets, which results in eight stable magnetic equilibria. In this addendum, we applied the same methodology to consider MTCs with 1, 2, 4, 8, 16, and 32 stable equilibria. We observe clear trends in the optimal values of the various MTC parameters as we change the number of magnets. We also find that the maximum synchronous torque grows asymptotically with the number of stable equilibria, with a diminishing return beyond 16.

Field implementations of fully underground sensor networks face many practical challenges that have limited their overall adoption. Power management is a commonly cited issue, as operators are required to either repeatedly excavate batteries for recharging or develop complex underground power infrastructures. Prior works have proposed wireless inductive power transfer (IPT) as a potential solution to these power management issues, but misalignment is a persistent issue in IPT systems, particularly in applications involving moving vehicles or obscured (e.g., underground) coils. 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. Overall, this work contributes to the field of underground sensor networks by successfully integrating a self-aligning wireless power delivery system with existing agricultural infrastructure. Furthermore, the alignment strategy presented in this work accomplishes coil misalignment correction without the need for complex sensor or coil architectures.

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.

Objective: We present a simple parameter, calculated from a single wearable sensor, that can be used to objectively measure disease severity in people with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) or Long COVID. We call this parameter UpTime. Methods: Prior research has shown that the amount of time a person spends upright, defined as lower legs vertical with feet on the floor, correlates strongly with ME/CFS disease severity. We use a single commercial inertial measurement unit (IMU) attached to the ankle to calculate the percentage of time each day that a person spends upright (i.e., UpTime) and number of Steps/Day. As Long COVID shares symptoms with ME/CFS, we also apply this method to determine Long COVID disease severity. We performed a trial with 55 subjects broken into three cohorts, healthy controls, ME/CFS, and Long COVID. Subjects wore the IMU on their ankle for a period of 7 days. UpTime and Steps/Day were calculated each day and results compared between cohorts. Results: UpTime effectively distinguishes between healthy controls and subjects diagnosed with ME/CFS ($\mathbf{p = 0.00004}$) and between healthy controls and subjects diagnosed with Long COVID ($\mathbf{p = 0.01185}$). Steps/Day did distinguish between controls and subjects with ME/CFS ($\mathbf{p = 0.01}$) but did not distinguish between controls and subjects with Long COVID ($\mathbf{p = 0.3}$). Conclusion: UpTime is an objective measure of ME/CFS and Long COVID severity. UpTime can be used as an objective outcome measure in clinical research and treatment trials. Significance: Objective assessment of ME/CFS and Long COVID disease severity using UpTime could spur development of treatments by enabling the effect of those treatments to be easily measured.

This paper presents 13.56 MHz inductive power transfer (IPT) through soil for sensors in agricultural applications. Two IPT system designs and their prototypes are presented. The first was designed for gathering data and observing the relationship between the performance of the coil driving circuits in response to water content, salinity, organic matter and compaction of the soil. The second prototype was designed as an application demonstrator, featuring IPT to an in-house sensor node enclosure buried 200 mm under the surface of an agricultural field. The results highlight that from the parameters studied, the combination of high salinity and high water content significantly increases the losses of the IPT system. The experiments demonstrate an over 40% rise in the losses from dc source to dc load after a 16% increase in soil water content and high salinity. In the technology demonstrator we mounted an IPT transmitter on a drone to wirelessly power an in-house bank of supercapacitors in the buried sensor-node enclosure. A peak power transfer of 30 W received at over 40% efficiency was achieved from a 22 V power supply on the drone to the energy storage under the ground. The coil separation in these experiments was 250 mm of which 200 mm correspond to the layer of soil. The coupling factor in all the experiments was lower than 5%. This system was trialled in the field for forty days and wireless power was performed five times throughout.

Wireless power transfer (WPT) has received increasing attention primarily as a means of recharging batteries in the last few decades. More recently, magnetoelectric (ME) structures have been investigated as alternative receiving antennas in WPT systems. ME structures can be particularly useful for small scale devices since their optimal size is much smaller than traditional receiving coils for a given operating frequency. WPT systems using ME laminate receivers have been shown to be helpful in wirelessly powering various sensors and biomedical implants. In recent years, a large number of studies have been conducted to improve the performance of ME composites, in which various configurations have been proposed, along with the use of different magnetostrictive and piezoelectric materials. In addition, many efforts have been devoted to miniaturizing ME devices. An essential obstacle to overcome is to eliminate the need for a DC bias field that is commonly required for the operation of ME structures. In this review paper, we will discuss the basic principle of ME effects in composites, materials currently in use, various ME receiver structures, performance measures, limitations, challenges, and future perspectives for the field of WPT. Furthermore, we propose a power figure of merit which we use to compare recent ME WPT research papers.

In this article, we apply dimensional analysis to the optimization of radial magnetic torque couplers. Our goal is to find the design that maximizes the torque potential in a given package size. We consider two types of torque coupler: the permanent-magnet (a.k.a. synchronous) torque coupler, in which both the inner and outer rotors contain permanent magnets; and the variable-reluctance torque coupler, in which the inner rotor contains permanent magnets and the outer rotor contains soft-magnetic teeth. Both types of torque coupler are defined by the same set of independent geometric and material parameters. First, the Buckingham $\Pi $ theorem is used to find the minimal set of dimensionless parameters required for design optimization. Then, using a combination of 2-D and 3-D finite-element analysis, we find and characterize the optimal designs. We explicitly consider torque couplers with eight stable magnetic equilibria (i.e., 45° of rotation between stable equilibria), but the methodology can be repeated for other configurations.

This article presents an investigation on the optimal design of a transmit coil for a wireless power transfer system (WPTS) for biomedical implants with the goal of maximizing the magnetic flux density (B-field) at the location of the implant while not violating magnetic field exposure limits. Maximizing the B-field correlates to higher transferable electric power for certain WPTSs, such as those that use magnetoelectric receivers. While previous works have optimized the thermal efficiency, or system efficiency, to our knowledge no one yet has developed the procedure to optimize the transmitter to maximize the B-field subject to an imposed safety limit constraint for magnetic field exposure. In addition to this safety constraint, the optimal design of the transmitter is considered when the system geometry or the input current is constrained. Equations for determining the design parameters of an optimal solenoid transmitter are derived subject to constraints on either transmitter size or electric current. If a certain magnetic field strength is required, solutions to the size and current of the transmitter are presented, which allow the desired fields without violating the safety constraint. The mathematical model is experimentally validated, and a case study is described that illustrates the optimal design rules.