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Wide bandgap Gallium Nitride (GaN) technology promises to deliver the next generation of power transistors capable of high energy density and compact design integration however, without active monitoring high failing rates are recorded due to its instability to design parameter variations. Moreover, the electromagnetic (EM) radiofrequency (RF) emissions due to GaN power switching require extra design resources. Considering the extensive research area dedicated to galvanic isolated magnetic sensors for GaN wafer monolithic integration with usage in power monitoring, this study investigates the conditions that a Hall sensor is required to meet when operating in close proximity of a GaN transistor. Through considerable experimental testing, it was determined that the sensor requires a magnetic field starting from ±1 mT when interfaced with a microcontroller. Additionally, since the GaN transistor’s EM RF switching noise was one of the most monitored parameters during the experiments, it was discovered that it is proportional to the transistor’s current transfer area whereas its magnitude is due to electrical current required by the load. As a result of these findings, the EM radiated switching noise may apply to all electrical switches and provide a significant advantage when designing for EM compatibility (EMC).

In this paper, a gallium nitride (GaN) magnetic Hall effect current sensor is simulated in 2D and 3D using the TCAD Sentaurus simulation toolbox. The model takes into account the piezoelectric polarization effect and the Shockley–Read–Hall (SRH) and Fermi–Dirac statistics for all simulations. The galvanic transport model of TCAD Sentaurus is used to model the Lorentz force and magnetic behaviour of the sensor. The current difference, total current, and sensitivity simulations are systematically calibrated against experimental data. The sensor is optimised using varying geometrical and biasing parameters for various ambient temperatures. This unintentionally doped ungated current sensor has enhanced sensitivity to 16.5 %T−1 when reducing the spacing between the drains to 1 μm and increasing the source to drain spacing to 76 μm. It is demonstrated that the sensitivity degrades at 448 K (S = 12 %T−1), 373 K (S = 14.1 %T−1) compared to 300 K (S = 16.5 %T−1). The simulation results demonstrate a high sensitivity of GaN sensors at elevated temperatures, outperforming silicon counterparts.

Abstract In order to overcome the drawbacks of the conventional protection methods in high‐voltage direct current transmission lines, a deep learning approach is proposed that directly learn the fault conditions based on unsupervised feature extraction to the detection and location decision by leveraging the hidden layer activations of recurrent neural network. The deep‐recurrent neural network boosting with the gated recurrent unit compared with the long short‐term memory unit is used by analysing both the signal presented in time domain and frequency domain. The proposed method is tested based on a modular multilevel converter based four‐terminal high‐voltage direct current system. Various faults under different conditions were simulated against fault resistance, external faults and small disturbance immunity with the validity, and the simulation verified a high accuracy, robustness and fast results because of the utilization of characteristic feature extraction.

Updating the road infrastructure requires the potential mass adoption of the road studs currently used in car detection, speed monitoring, and path marking. Road studs commonly include RF transceivers connecting the buried sensors to an offsite base station for centralized data management. Since traffic monitoring experiments through buried sensors are resource expensive and difficult, the literature detailing it is insufficient and inaccessible due to various strategic reasons. Moreover, as the main RF frequencies adopted for stud communication are either 868/915 MHz or 2.4 GHz, the radio coverage differs, and it is not readily predictable due to the low-power communication in the near proximity of the ground. This work delivers a reference study on low-power RF communication ranging for the two above frequencies up to 60 m. The experimental setup employs successive measurements and repositioning of a base station at three different heights of 0.5, 1 and 1.5 m, and is accompanied by an extensive theoretical analysis of propagation, including line of sight, diffraction, and wall reflection. Enhancing the tutorial value of this work, a correlation analysis using Pearson’s coefficient and root mean square error is performed between the field test and simulation results.

As the RF communication on 18650 Li-ion cell level has not been reported due to its challenges and constrains, in this work, a valid wireless data link is demonstrated in an enclosed empty metal shell at 868 MHz and 2.4 GHz based on the IEEE 802.15.4 standard. The experimental tests are carried out using two generic unturned radiative structures, a wire loop fitted inside a cell shell, and an open terminal sub miniature version A (SMA), subsequently oriented vertically and horizontally relative to the ground plane. Based on signal strength indicator, bit error rate, and packet error rate, the test characterized a payload of 120 bytes at the highest speed of 150 kbps and 250 kbps supported by the IEEE 802.15.4 for the two communication frequencies. A MATLAB simulation is used in parallel to determine the three-dimensional radiative pattern of the two structures, whereas a three-ray model for multipath range propagation is implemented to complete the empirical experiments. It was demonstrated through testing communication of up to 10 m for both operating frequencies, proving the concept of wireless cell communication within short ranges, an essential feature for monitoring the health of each cell inside future electric vehicles (EVs).

Efficient management through monitoring of Li-ion batteries is critical to the progress of electro-mobility and energy storage globally, since the technology can be hazardous if pushed beyond its safety boundaries. Battery management systems (BMSs) are being actively improved to reduce size, weight, and cost while increasing their capabilities. Using power line communication, wireless monitoring, or hybrid data links are one of the most advanced research directions today. In this work, we propose the use of radio frequency (RF) transceivers as a communication unit that can deliver both wired and wireless services, through their superior analog and digital signal processing capability compared to PLC technology. To validate our approach computational simulation and empirical evaluation was conducted to examine the possibility of using RF transceivers on a direct current (DC) bus for wired BMS. A key advantage of this study is that it proposes a flexible and tested system for communication across a variety of network scenarios, where wireless data links over disrupted connections may be enabled by using this technology in short-range wired modes. This investigation demonstrates that the IEEE 802.15.4-compliant transceivers with operating frequencies of 868 MHz and 2.4 GHz can establish stable data links on a DC bus via capacitive coupling at high data rates.

In anticipation of the hybrid utilisation of the radio frequency (RF) wireless transceiver technology embedded in future smart Li-ion battery cells to deliver hybrid links based on power line communication (PLC) and wireless connections, herein we present an empirical high-frequency investigation of the direct current (DC) bus. The focus is to determine, via statistical tools including correlation coefficient (CC), root mean squared error (RMSE) and feature selective validation (FSV) method, the impedance and signal change impact on a possible communication link when fully charged cells are present or completely missing from the bus. Moreover, to establish if technological differences may be accounted for during the empirical experiments, Li-ion cells from two different manufacturers were selected and connected via three subsequent capacitive couplings of 1 µF, 1 nF and 1 pF. According to a methodical comparison by employing CC, RMSE, and FSV over the measured impedance and signal attenuation, this study has shown that the physical DC network is the dominant impedance at high frequencies and that the signal attenuation on the DC line supports communication in the investigated spectrum. The reported findings are critical for in situ hybrid PLC and wireless communication implementation of BMS for Li-ion systems supported through only one RF transceiver.