Hybrid Approach for Performance Optimization of Gallium Nitride High Electron Mobility Transistors Small‐Signal Behavioral Models

Recently, Global Optimization algorithms are becoming an efficient tool to solve complicated problems for various applications. Modern optimization algorithms like Black Hole Optimization (BHO) and Social Spider Optimization (SSO) algorithms are widely used to solve different problems. This paper is demonstrating the applicability of these techniques for training an artificial neural network (ANN) and finding optimal values for the weights and biases. The proposed optimization-based ANN model has been utilized to model the IV characteristics of Gallium Nitride High Electron Mobility Transistor (GaN HEMT). A very good fitting is obtained with measurements which shows the validity of both BHO and SSO for this application.

In this paper, an efficient Support Vector Regression (SVR) and Artificial Neural Network (ANN) based IV models for Gallium Nitride High Electron Mobility Transistors (GaN HEMT) is proposed. The modeling approaches are applied on pulsed IV measurements of a standard size 1-mm GaN HEMT at four different ambient temperatures of 25, 40, 55, and 70°C. A non-parametric based Bayesian optimization is exploited to optimize the hyper parameters of SVR & subsequently improve its prediction capability. The two models were evaluated it terms of the mean squared error and their ability to accurately predict the IV characteristics. An excellent agreement with the measurement has been obtained over the entire operational regions of the transistor. Analytical formulas for the drain current based on both models have been provided and it can be easily implemented in standard CAD software.

A 50 W dual‐band high‐efficiency gallium nitride (GaN) high electron mobility transistor (HEMT) power amplifier with a three‐stage L‐type DC bias circuit capable of individually adjusting second‐harmonic impedances is proposed for 1.8 and 2.6 GHz frequencies. The output network of this power amplifier is composed of an output matching network comprising five‐stage transmission lines and a three‐stage L‐type DC bias circuit with three L‐type circuits and one transmission line. The one‐stage L‐type circuit comprises a series transmission line and a quarter‐wavelength open‐ended shunt stub. For the high‐efficiency performance of the power amplifier, the output matching network is matched to the optimum impedances of the fundamental frequencies, and the DC bias circuit optimizes the impedances individually at the second‐harmonic frequencies without affecting the matched fundamental frequency impedances in the output matching network. Measured results show that the proposed dual‐band GaN HEMT power amplifier achieved gains of 15.6 and 13.8 dB as well as maximum power‐added efficiencies of 70.5% and 66.3% with 47 dBm output power at 1.8 and 2.6 GHz, respectively.

Gallium Nitride (GaN) high electron mobility transistor (HEMT) is one of the promising candidates to replace existing switches in high-frequency high power converter applications. Reliability of GaN HEMT is an important issue for its commercial deployment. Online prognosis of this transistor ensures robust reliability for mission critical applications. Online prognosis requires identification of fault precursors which shows sensitivity to degradation. Although gate threshold voltage and gate leakage current are identified as fault precursors, Extraction methods of these parameters are offline. In this paper, on-state resistance (R DS, ON ) is investigated as an online fault precursor for GaN HEMT. Temperature variation during its operation results in irreversible damage to GaN HEMT. Adaptive thermal network based temperature estimation method using Extended Kalman Filter (EKF) is also proposed. A sequential Monte-Carlo simulation based data driven remaining useful life (RUL) estimation method is also proposed which can be applicable for schedule maintenance before breakdown. Experimental validation of these proposed methods have been presented.

In this work, a novel gallium nitride/aluminium gallium nitride (GaN/AlGaN) high electron mobility transistor (HEMT) structures, such as TiN as Schottky contact, HEMT with TiN as Schottky contact, and AlInGaN barrier layer are propounded and have analyzed its DC, RF performance parameters in comparison with SiO2‐based metal‐oxide‐semiconductor high electron mobility transistor (MOSHEMT) utilizing Synopsys Sentaurus technology computer‐aided design (TCAD) simulator. HEMT with TiN as Schottky contact and AlInGaN barrier layer is showing peak transconductance (Gm) of 135 mS mm−1, which is higher than HEMT with TiN as Schottky contact, that is, 117 mS mm−1. The device with TiN Schottky gate contact for the HEMT exhibits high cutoff frequency (fT = 20 GHz) and maximum oscillation frequency (fmax = 94.6 GHz) when compared with SiO2‐based MOSHEMT (fT = 12.8 GHz, fmax = 27.5 GHz). Introducing the AlInGaN barrier layer for the TiN Schottky contact‐based HEMT further increased the cutoff frequency (fT = 59.6 GHz) and maximum oscillation frequency (fmax = 324 GHz), indicating high frequency operation range for communication applications.

Gallium nitride high electron mobility transistor (GaN HEMT) has matured dramatically over the last few years. More and more devices have been manufactured and field in applications ranging from low power voltage regulator to high power infrastructure base-stations. Compared to the state of art silicon MOSFET, GaN HEMT has much better figure of merit and is potential for high frequency application. In general, 600V GaN HEMT is intrinsically normally-on device. To easily apply depletion mode GaN HEMT in circuit design, a low voltage silicon MOSFET is in series to drive the GaN HEMT, which is well known as cascode structure. This paper studies the characteristics and operation principles of 600V cascode GaN HEMT. Evaluations of GaN HEMT performance based on Buck converter under hard-switching and soft-switching conditions are presented. Experimental results illustrate that GaN HEMT is superior than silicon MOSFET but still needs soft-switching in high frequency operation due to considerable package and layout parasitic inductors and capacitors. Then GaN HEMT is applied to a 1MHz 300W 400V/12V LLC converter. Comparison of experimental results with state of art silicon MOSFET is provided to validate the advantages of GaN HEMT.

In the fabrication process of wide bandgap gallium nitride high electron mobility transistors (GaN HEMT), due to the process error, process fluctuation, material defects, and other factors, wide bandgap semiconductor transistors produced in different batches will also have dispersed fluctuation of electrical characteristics under these special working conditions, which results in deviations between ideal software simulation parameters based on device model and the actual measurement parameters. Some statistical analysis methods like principal component analysis, factor analysis, and multivariate statistical regression in this article are introduced to process S-parameter which can be measured from different batches of CGH40010 GaN HEMT and statistical model parameters can be got from them. Error of S-parameter comparison are less than 10% between calculation results of established small-signal statistical equivalent circuit model (ECM) and S-parameter sample measurement results. Monte Carlo simulation based on statistical model can be well adopted to predict dispersed fluctuation of electrical characteristics for different samples and which can be used as the basis of large-signal ECM statistical model.

The testing and modeling of semiconductor devices are the foundation of circuit design. The issue of high-power device testing urgently needs to be solved as the power level of the devices under test (DUTs) increases. This work proposes advanced measurement methods based on three aspects of "measuring capability, security, and stability" with a focus on the features of high output power, easy self-oscillation in mismatch tests, and safety risk in the measurement system of high-power transistors. In this paper, the wideband limiter and bias filter network are innovatively introduced to improve the stability and security of the measurement circuit. Meanwhile, the output signal of the DUT is suggested to be measured using a spectrum analyzer before the test to avoid damage to the circuit caused by the possible self-oscillation of the transistor. Moreover, an efficient test system of current parameters and S-parameters is developed, with coaxial fixtures offered to boost the test power capacity and cascade bridges adapted to satisfy the pulse operating conditions. Finally, based on the improved test methods, a gallium nitride high electron mobility transistor (GaN HEMT) with a gate width of 400 × 32μm and a power density of roughly 10 W/mm was tested. A relatively complete I-V curve and a S-parameter curve were obtained, demonstrating the effectiveness and applicability of the improved methods.

Resonant driving scheme for p-doped gallium nitride high electron mobility transistor to reduce driving power loss

Ultra-fast switching speed and low switching loss of the gallium nitride high electron mobility transistors enable the realisation of high power density converter with excellent conversion efficiency. However, the rapid switching transition leads to significant overshoot and crosstalk issues that can degrade the performance of the devices. To facilitate the evaluation of these effects on low-voltage gallium nitride devices, this paper develops an analytical model to predict overshoot and crosstalk during switching transitions accurately and efficiently. The model is constructed based on the detailed circuit deduction of various stages of the device's switching process. It also considers the voltage-dependent junction capacitances as well as the forward and the reverse transconductances. The simulated results obtained from the model are validated experimentally. With the model, the impacts of parasitic elements, especially the power loop inductance, on voltage/current overshoots and spurious voltage due to crosstalk can be easily evaluated, which provides valuable design guidelines for power conversion applications using low-voltage gallium nitride high electron mobility transistor.

Gallium nitride high electron mobility transistor (GaN HEMT) has matured dramatically over the last few years. A progressively larger number of GaN devices have been manufactured for in field applications ranging from low power voltage regulators to high power infrastructure base-stations. Compared to the state-of-the-art silicon MOSFET, GaN HEMT has a much better figure of merit and shows potential for high-frequency applications. The first generation of 600 V GaN HEMT is intrinsically normally on device. To easily apply normally on GaN HEMT in circuit design, a low-voltage silicon MOSFET is in series to drive the GaN HEMT, which is well known as cascode structure. This paper studies the characteristics and operation principles of a 600 V cascode GaN HEMT. Evaluations of the cascode GaN HEMT performance based on buck converter at hard-switching and soft-switching conditions are presented in detail. Experimental results prove that the cascode GaN HEMT is superior to the silicon MOSFET, but it still needs soft-switching in high-frequency operation due to considerable package and layout parasitic inductors and capacitors. The cascode GaN HEMT is then applied to a 1 MHz 300 W 400 V/12 V LLC converter. A comparison of experimental results with a state-of-the-art silicon MOSFET is provided to validate the advantages of the GaN HEMT.

An accurate, efficient, and improved Light Gradient Boosting Machine (LightGBM) based Small‐Signal Behavioral Modeling (SSBM) techniques are investigated and presented in this paper for Gallium Nitride High Electron Mobility Transistors (GaN HEMTs). GaN HEMTs grown on SiC, Si and diamond substrates of geometries 2 × 50 , 10 × 200 , and 4 × 125 , respectively are used in this study. A versatile set of LightGBM's hyperparameters including learning and tree specific parameters are meticulously optimized using a modern and vigorous optimization algorithm namely Osprey Optimization Algorithm (OOA) with the objective to accomplish superior model performance. The developed OOA‐LightGBM based models are validated for a wide array of operating conditions including for frequency values within a broad spectrum of 0.25 to 120 GHz, 0.1 to 26 GHz, and 0.1 to 40 GHz for GaN‐on‐SiC, GaN‐on‐Si, and GaN‐on‐Diamond HEMTs, respectively. The proposed SSBM techniques have demonstrated remarkable prediction ability and are impressively efficient for all the GaN HEMTs devices tested in this work.

The Compact Model Coalition (CMC), a part of the Silicon Integration Initiative (Si2), is standardizing a compact model for Gallium Nitride High Electron Mobility Transistors (GaN HEMTs). After a global search for model candidates, eight were selected to present at a CMC meeting. In the next phase, selected candidates will be evaluated for their ability to fit a common set of hardware data. After a third round of more comprehensive testing, a standard GaN HEMT model will be selected.

In the past few decades, circuits based on gallium nitride high electron mobility transistor (GaN HEMT) have demonstrated exceptional potential in a wide range of high-power and high-frequency applications, such as the new generation mobile communications, object detection, consumer electronics, etc. As a critical intermediary between GaN HEMT devices and circuit-level applications, GaN HEMT large-signal models play a pivotal role in the design, application and development of GaN HEMT devices and circuits. This review provides an in-depth examination of the advancements in GaN HEMT large-signal modeling in recent decades. Detailed and comprehensive coverage of various aspects of GaN HEMT large-signal model are offered, including large-signal measurement setups, classical formulation methods, model classification, non-ideal effects, etc. In order to better serve follow-up research, this review also explores potential future directions for the development of GaN HEMT large-signal modeling.

Gallium nitride high electron mobility transistor (GaN HEMT) is liable to gate false turn-on problem when the gate crosstalk voltage exceeds its threshold voltage in the widely adopted phase-leg topology due to its low threshold voltage and high switching speed. Without considering the gate loop stray inductance, gate internal resistance, nonlinearity of parasitic capacitances and power loop stray parameters, traditional false turn-on analytical method is insufficient to support accurate analysis. And it has been found that GaN HEMT gate-source parasitic capacitance C <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">gs</sub> previously assumed constant is otherwise highly nonlinear and has strong impacts on the gate crosstalk voltage. This paper has measured C <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">gs</sub> by vector network analyzer and constructed an accurate nonlinear model of C <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">gs</sub> , based on which an accurate GaN HEMT behavior model is further fulfilled. The accuracy of the proposed behavior model has been verified by large amounts of experiment results. The proposed GaN HEMT model is used to accurately calculate gate crosstalk voltage and switching losses. Besides, false turn-on induced extra loss has been calculated and is adopted as a criterion to evaluate the severity of false turn-on and optimal design method for false turn-on suppression has been detailed further.