Wireless Power Transfer System for Mobile Robots via Magnetic Resonant Coupling with Impedance Matching

Wireless power transfer via magnetic resonant coupling can be used to supply power to a mobile robot within a few meters of a transmitter coil. However, when the robot moves or its power consumption fluctuates, its input impedance varies and causes power reflection. Therefore, we propose the use of a driver coil on the transmitter side to match the input impedance. The input impedance is matched and power reflection is eliminated by regulating the coupling coefficient between the driver and the transmitter. During experiments, the transmitting efficiency showed good agreement with the calculated value, and the input impedance was matched under varying distances and load resistances. Therefore, the proposed system was demonstrated to solve the power reflection problem in mobile robots.

MODELING THE ANTENNA INPUT IMPEDANCE BY THE METHOD OF MOMENTS

The paper presents a comparison of excitation source models when modeling antennas by the method of moments. By using a set of adjacent edges when specifying the impact, it is possible to obtain correct results when the computational grid of the antenna model is more frequent. This is shown on the example of a symmetric electric vibrator.

High Impedance Amplifiers for Non-Contact Bio-Potential Sensing

<p>This research develops a non-contact bio-potential sensor which can quickly respond to input transient events, is insensitive to mechanical disturbances, and operates with a bandwidth from 0.04Hz – 20kHz, with input voltage noise spectral density of 200nV / √Hz at 1kHz. Initial investigations focused on the development of an active biasing scheme to control the sensors input impedance in response to input transient events. This scheme was found to significantly reduce the settling time of the sensor; however the input impedance was degraded, and the device was sensitive to distance fluctuations. Further research was undertaken, and a circuit developed to preserve fast settling times, whilst decreasing the sensitivity to distance fluctuations. A novel amplifier biasing network was developed using a pair of junction field effect transistors (JFETs), which actively compensates for DC and low frequency interference, whilst maintaining high impedance at signal frequencies. This biasing network significantly reduces the settling time, allowing bio-potentials to be measured quickly after sensor application, and speeding up recovery when the sensor is in saturation. Further work focused on reducing the sensitivity to mechanical disturbances even further. A positive feedback path with low phase error was introduced to reduce the effective input capacitance of the sensor. Tuning of the positive feedback loop gain was achieved with coarse and fine control potentiometers, allowing very precise gains to be achieved. The sensor was found to be insensitive to distance fluctuations of up to 0.5mm at 1Hz, and up to 2mm at 5kHz. As a complement to the non-contact sensor, an amplifier to measure differential bio-potentials was developed. This differential amplifier achieved a CMRR of greater than 100dB up to 10kHz. Precise fixed gains of 20±0:02dB, 40±0:01dB, 60±0:03dB, and 80±0:3dB were achieved, with input voltage noise density of 15nV / √Hz at 1kHz.</p>

High Impedance Amplifiers for Non-Contact Bio-Potential Sensing

<p>This research develops a non-contact bio-potential sensor which can quickly respond to input transient events, is insensitive to mechanical disturbances, and operates with a bandwidth from 0.04Hz – 20kHz, with input voltage noise spectral density of 200nV / √Hz at 1kHz. Initial investigations focused on the development of an active biasing scheme to control the sensors input impedance in response to input transient events. This scheme was found to significantly reduce the settling time of the sensor; however the input impedance was degraded, and the device was sensitive to distance fluctuations. Further research was undertaken, and a circuit developed to preserve fast settling times, whilst decreasing the sensitivity to distance fluctuations. A novel amplifier biasing network was developed using a pair of junction field effect transistors (JFETs), which actively compensates for DC and low frequency interference, whilst maintaining high impedance at signal frequencies. This biasing network significantly reduces the settling time, allowing bio-potentials to be measured quickly after sensor application, and speeding up recovery when the sensor is in saturation. Further work focused on reducing the sensitivity to mechanical disturbances even further. A positive feedback path with low phase error was introduced to reduce the effective input capacitance of the sensor. Tuning of the positive feedback loop gain was achieved with coarse and fine control potentiometers, allowing very precise gains to be achieved. The sensor was found to be insensitive to distance fluctuations of up to 0.5mm at 1Hz, and up to 2mm at 5kHz. As a complement to the non-contact sensor, an amplifier to measure differential bio-potentials was developed. This differential amplifier achieved a CMRR of greater than 100dB up to 10kHz. Precise fixed gains of 20±0:02dB, 40±0:01dB, 60±0:03dB, and 80±0:3dB were achieved, with input voltage noise density of 15nV / √Hz at 1kHz.</p>

Wave Number and Input Impedance of a VLF Insulated Linear Antenna in an Anisotropic Ionosphere

We report a method to obtain the wave number and input impedance of a very low frequency (VLF) insulated linear antenna in an anisotropic ionosphere. Due to the anisotropy, electromagnetic fields in the ionosphere are decomposed into the ordinary wave and extraordinary wave. Wave equations for the layered structure are applied to access the wave number of the insulated antenna in the ionosphere via the derivation of the eigenvalue equation by using boundary conditions. The expression for the wave number is given based on some approximation formulas. Then, King’s antenna theory is further employed to solve the input impedance and current distribution of the antenna in the anisotropic medium. After the validation of the method is performed, near-field characteristics for an insulated antenna with different medium parameters in the anisotropic ionosphere are discussed. Effects of the electric density and geomagnetic field of the time-and space-varying anisotropic ionosphere on the distribution of normalized current are analyzed. This finding provides a promising avenue for getting electromagnetic characteristics of space-borne antennas.

Sensorless metal object detection for wireless power transfer using machine learning

Purpose This study aims to realize a sensorless metal object detection (MOD) using machine learning, to prevent the wireless power transfer (WPT) system from the risks of electric discharge and fire accidents caused by foreign metal objects. Design/methodology/approach The data constructed by analyzing the input impedance using the finite element method are used in machine learning. From the loci of the input impedance of systems, the trained neural network (NN), support vector machine and naive Bayes classifier judge if a metal object exists. Then the proposed method is tested by experiments too. Findings In the test using simulated data, all of the three machine learning methods show high accuracy of over 80% for detecting an aluminum cylinder. And in the experimental verifications, the existence of an aluminum cylinder and empty can are successfully identified by a NN. Originality/value This work provides a new sensorless MOD method for WPT using three machine learning methods. And it shows that NNs obtain high accuracy than the others in both simulated and experimental verifications.