Voltage Variations Research Articles

Optimization Conditions for High-Power AlGaN/InGaN/GaN/AlGaN High-Electron-Mobility Transistor Grown on SiC Substrate

In this study, we aimed to propose an optimal structure for an AlGaN/InGaN/GaN/AlGaN/SiC HEMT by investigating how the breakdown voltage varies with the thickness and composition of the InGaN layer. The breakdown voltage was shown to be highly dependent on the In composition. Specifically, as the In composition increased, the breakdown voltage rapidly increased, but it exhibited saturation when the In composition exceeded 0.06. Therefore, it is desirable to maintain the In composition at or above 0.06. The variation in breakdown voltage due to thickness was relatively small compared to the variation caused by In composition. While the breakdown voltage remained nearly constant with increasing thickness, it began to decrease when the thickness exceeded 10 nm. Hence, the thickness should be kept below 10 nm. Additionally, as the In composition increased, the subthreshold swing (SS) also increased, but the drain current value was shown to increase. On the other hand, it was observed that the SS value in the transfer characteristics and the current–voltage characteristics were almost unaffected by the thickness of the InGaN layer.

Efficient voltage control strategy: observability design for multistage DC–DC buck converter

This paper emphasizes the significance of implementing an effective control system to enhance the performance of a three-stage DC–DC buck converter (TDDC). Herein, we present the development of an observer controller (OC) for TDDC, where average modeling of the DC–DC converter was employed alongside an observer algorithm for the OC. The primary focus is on the adoption of an observation topology aimed at enhancing system responsiveness under various conditions, including variable input voltages, reference voltage changes, load fluctuations, integration with photovoltaics, and battery charging. This approach ensures improved stability and performance, addressing the dynamic challenges inherent in such systems. A comparative analysis was conducted on two distinct control topologies for the proposed TDDC system, namely proportional–integral (PI) and advanced OC. Simulink software was used to model and simulate the proposed system. The results demonstrate lower rising and settling times of the TDDC for the OC and PI implementations, respectively. Additionally, the system with the OC eliminates 20% of the overshoot, while the system with OC minimizes the output voltage oscillations from 13% to 2% compared to the PI system. The OC was integrated into the TDDC to enhance system stability and improve the control loops, particularly the third loop. These improvements make the TDDC with OC suitable for application to renewable energy systems, microgrids, telecommunication networks, and electric vehicles, where precise control and stability are essential.

Integral Sliding Mode‐Composite Nonlinear Feedback Control Strategy for Microgrid Inverter Systems

To enhance the dynamic performance and robustness of the voltage control system of islanded microgrid inverters, a new control strategy combining integral sliding mode (ISM) control and composite nonlinear feedback (CNF) control is proposed. In ISM control, firstly, a new reaching law is designed to improve movement quality in the reaching phase by improving the power term and introducing the inverse tangent function. Then, to improve disturbance observation accuracy, a variable gain extended state observer is designed by improving the regulation mechanism of the state variables according to deviation control. Using the idea of variable damping, linear and nonlinear feedback are combined into CNF control. Specifically, linear feedback provides a small damping ratio for faster system response, while nonlinear feedback increases the damping ratio to improve steady‐state performance. Simulation results show that the integral sliding mode‐composite nonlinear feedback (ISM‐CNF) control strategy cam balances convergence speed and chattering better and achieves higher steady‐state accuracy than conventional strategies. Moreover, ISM‐CNF control has better robustness to reference voltage variations and disturbances caused by sudden load changes. Therefore, the ISM‐CNF control strategy can accomplish voltage control of islanded microgrid inverters quickly and steadily, effectively suppressing system disturbances and enhancing stability and power quality. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Intelligent fault diagnosis in power distribution networks using LSTM-DenseNet network

This paper introduces a novel fault diagnosis method that combines DenseNet and Long Short-Term Memory (LSTM) networks. The DenseNet utilizes its unique dense block structure to detect subtle variations in three-phase voltage and zero-sequence current signals. In addition, the Squeeze-and-Excitation (SE) module is introduced in DenseNet. The SE module enhances DenseNet's feature representation by adapting the importance of each channel in the feature map. Furthermore, integrating the LSTM model enables capturing time-domain features of fault signals, enhancing the analysis of waveform changes and trends. These extracted features are subsequently fused in a cascaded manner, leveraging the strengths of both approaches to obtain a more comprehensive information representation. To better explain the capability of feature extraction in each part of the model, t-distributed Stochastic Neighbor Embedding (t-SNE) method is used for visual analysis. The proposed method is evaluated using two distribution network models, namely the 10 kV and IEEE34 networks, in simulation. The verification results indicate that the proposed method achieves exceptionally high accuracy in fault identification for both tested distribution network models, with rates of 99.87 % and 99.82 %, respectively, while also demonstrating robust performance in noisy environments. This performance surpasses that of other related methods, underscoring the enhanced effectiveness of our approach.

A Robust Low‐Power Power‐On‐Reset Circuit With Dual Threshold Method

ABSTRACTIn this paper, a robust low‐power power‐on‐reset (POR) circuit with dual threshold method is proposed. The current‐based circuit exhibits good robustness with respect to process, voltage, temperature, and supply ramp variations. In contrast to conventional delay‐based pulse generation approaches, a dual threshold method is introduced to generate POR and brown‐out‐reset (BOR) pulse signals, resulting in ultralow quiescent current and a compact area. Implemented in the 55‐nm CMOS process, the proposed circuit achieves an accurate trigger‐point voltage with a temperature coefficient of 90.4 ppm/°C and a deviation to the ramp time of 2.9% for a range from 100 μs to 1 s. Furthermore, the quiescent current and active area are 0.3 nA and 4834 μm2, respectively, making it particularly suitable for energy harvesting systems.

Complex Reflectivity Modulation Characteristics at Visible Wavelength Using Liquid Crystal on a Metasurface Device

Active metasurface device capable of complex modulation in the visible light range is demonstrated. To realize complex modulation, a liquid crystal (LC) of twisted nematic mode on a plasmonic antenna metasurface, where resonance wavelength is sensitive to its geometry and nearby optical environment, is integrated. For the LC process on the metasurface, the alignment characteristics of the material exposed to the LC on the metasurface are first identified and the polyimide alignment layer is omitted. The LC works in twisted nematic mode to enhance complex modulation characteristics. The complex reflectivity coefficient is measured while varying the voltage applied to both the antenna and metal electrode in the visible light region. Complex reflectivity into a doughnut shape with a small voltage variation of 3.1 V on the antenna electrode and 2.5 V on the metal electrode is successfully modulated. The largest complex modulation is achieved at a wavelength of 660 nm, with phase and reflectivity amplitude modulations of 0–2π radian in a doughnut shape and 0.3 and 0.6, respectively. So far true holographic experience is limited by high‐order overlapping and twin images. Through this approach, a technical method is suggested for overcoming such obstacles and accomplishing advanced holographic display.

Early Warning of Energy Storage Battery Fault Based on Improved Autoformer and Adaptive Threshold

To enhance voltage prediction accuracy in energy storage batteries and address the limitations of fixed threshold warning methods, a fault warning approach based on an improved Autoformer model and adaptive thresholds is proposed. First, a spatiotemporal filtering layer is introduced into the autocorrelation mechanism to analyze the trend features of voltage sequences across different frequency domains. Additionally, an adaptive gating residual connection is used to link the sublayer and current layer output features, which helps to improve the model's adaptive feature selection capability. This innovation enables the development of a robust voltage prediction model based on the enhanced Autoformer. Then, a similarity‐based adaptive threshold, using interval estimation, is employed to rapidly track variations in battery voltage, enabling dynamic adjustment of voltage thresholds. Finally, the proposed method is validated with real voltage data from an operational energy storage station. The experimental results shows that the proposed model has higher accuracy and robustness compared to similar methods. The adaptive threshold can reduce the false alarm rate by ≈18% and issue alarms at three sampling points ahead of the battery management system alarm, improving fault warning accuracy and illustrating that early fault warning is effectively and practically carried out using the method.

AQUILA OPTIMIZED NONLINEAR CONTROL FOR DC-DC BOOST CONVERTER WITH CONSTANT POWER LOAD

Constant power loads (CPL) can be operated by tight-controlled power electronic converters, which have negative impedance and absorb continuous power. Constant power load creates instability in an open-loop system because of its negative incremental impedance. To tackle this problem, a discrete sliding-mode (AQO-DSM) nonlinear control technique has been proposed for a DC-DC boost converter fed CPL based on Aquila optimization. In this paper, the proposed AQO-DSM controllers provide the system stability during a steady state and maintain output voltage regardless of input voltage or CPL variations. In this case, the DSM controller of a DC-DC boost converter's characteristics are adjusted using the Aquila optimization method (AQO). The Lyapunov stability concept is utilized to assess the system's overall stability. Under various system operating conditions, an experimental study and simulation are carried out to validate the proposed controller. The existing methods, such as sliding mode controller (SMC), fuzzy-based SMC (F-SMC), and super twisting algorithm (STA)-based SMC strategies, are compared with a proposed plan to demonstrate the superiority of the proposed AQO-DSMC. Simulated and experimental results have shown that the AQO-DSMC achieves the fastest convergence, the smallest steady-state, settling time under loaded conditions, and consistent chatter reduction compared with all contrasted control methods.

Controller Area Network (CAN) Bus Transceiver with Authentication Support and Enhanced Rail Converters

This paper presents an advanced Controller Area Network (CAN) bus transceiver designed to enhance security using frame-level authentication with the concept of a nonphysical virtual auxiliary data channel. We describe the newly conceived transceiver security features and provide results concerning the design, implementation, fabrication and test of the transceiver to validate its functionality and robust operation in the presence of systemic error sources including Process, Voltage, and Temperature (PVT) variations. The virtual auxiliary channel integrates CAN frame authentication signatures into the primary data payload via phase modulation while also providing compatibility with existing CAN protocols, interoperability with non-enhanced systems and requiring no network or software modifications. Enhanced rail converters are designed to facilitate single-rail to dual-rail data conversion and vice versa, preserving phase information and minimizing phase errors across various nonideal effects such as frequency drift, Process, Voltage, and Temperature (PVT) variations, and cable phase mismatch. This ensures reliable data transmission and robust authentication in the presence of adversarial cyberattacks such as packet injection. The receiver recovers both the CAN frame data and the security signature, comparing the latter with an authorized signature to provide a real-time “GO/NO_GO” signal for verifying packet authenticity and without exceeding the CAN clock jitter specifications.

Hybrid energy system optimization integrated with battery storage in radial distribution networks considering reliability and a robust framework

This research presents a robust optimization of a hybrid photovoltaic-wind-battery (PV/WT/Batt) system in distribution networks to reduce active losses and voltage deviation while also enhancing network customer reliability considering production and network load uncertainties. The best installation position and capacity of the hybrid system (HS) are found via an improved crow search algorithm with an inertia weight technique. The robust optimization issue, taking into account the risk of uncertainty, is described using the gap information decision theory method. The proposed approach is used with 33- and 69-bus networks. The results reveal that the HS optimization in the network reduces active losses and voltage variations, while improving network customer reliability. The robust optimization results show that in the 33-bus network, the system remains resilient to prediction errors under the worst-case uncertainty scenario, with a 44.53% reduction in production and a 22.18% increase in network demand for a 30% uncertainty budget. Similarly, in the 69-bus network, the system withstands a 36.22% reduction in production and a 16.97% increase in load for a 25% uncertainty budget. When comparing stochastic and robust methods, it was found that the stochastic Monte Carlo method could not consistently provide a reliable solution for all objectives under uncertainty, whereas the robust approach successfully managed the maximum uncertainty related to renewable generation and network demand across different uncertainty budgets.

Second‐Harmonic Ripple in Two‐Stage Single‐Phase Photovoltaic Inverters: Analysis and Mitigation

ABSTRACTTwo‐stage single‐phase photovoltaic inverters exhibit a second‐harmonic ripple at the dc‐link voltage, which can cause variations in the terminal voltage of the photovoltaic array, reducing the efficiency of the maximum power point tracking (MPPT). Initially, this work investigates the efficiency reduction caused by the second‐harmonic component using analytical models. Besides, this work explores a control technique to reduce the ripple in the terminals of the photovoltaic module based on real‐time normalization of the dc/dc converter control signal. This technique is compared with conventional control and with the addition of second‐harmonic resonant control. The case study is based on a 4.4‐kVA/220‐V photovoltaic inverter with input for two photovoltaic strings. The results indicate that both techniques are capable of performing the attenuation of the voltage ripple at the terminals of the photovoltaic array, resulting in efficiency gains in the order of 0.74% for the strategy based on resonant control and 0.95% for the proposed normalization technique. In addition, C‐HIL and experimental results prove the reduction in voltage ripple with the normalization and resonant control. As an advantage, the normalization technique is simpler than the second one, because it does not require modification of the control structure of the dc/dc converter.

Quantitative evaluation of the effects of dual-energy CT acquisition, reconstruction and postprocessing parameters on virtual Non-Calcium (VNCa) images

PurposeThe appearance and associated interpretation of Virtual Non-Calcium (VNCa) images extracted from dual-energy CT (DECT) acquisitions are influenced by many parameters. This study aimed to investigate the effects of acquisition, reconstruction, and postprocessing parameters on VNCa images. Material and methodsA human cadaver leg was scanned using a dual-source DECT scanner, with variations in tube current, tube voltage, reconstruction kernels, and post-processing settings (resolution, upper threshold, lower threshold, beam-hardening correction). The impact of noise was investigated by scanning the specimen five times using the same standard acquisition, reconstruction and postprocessing parameters. VNCa values were measured in four different regions of interest within different bones. ResultsTube current and reconstruction kernels had no significant effect on VNCa values, with maximal standard deviations of 6.2 and 6.1 HU respectively. However, reducing the kVp difference between both tubes, reduced the spectral separation which resulted in lower VNCa values. For postprocessing parameters, variations in resolution and lower and upper thresholds as well as applying beam-hardening correction showed a large impact on VNCa values. ConclusionThe results of this study improve the understanding of the impact of certain CT parameters on VNCa images. Tube voltage and post-processing settings have a large impact on VNCa values. An inappropriate choice of threshold range, resolution and incorrect use of calcium beam-hardening correction can potentially lead to false positive findings of bone marrow edema. This can furthermore impact the ability to compare results from the literature and between institutions, which emphasizes the importance of optimizing and standardizing acquisition, reconstruction and postprocessing parameters for consistent VNCa imaging.

Lightweight High-Throughput True Random Number Generator Based on State Switchable Ring Oscillator

True random number generators (TRNGs) perform an extremely critical role in cryptographic algorithms and security protocols, scientific simulation, industrial testing, privacy protection, and numerous other domains. Nevertheless, modern TRNGs have difficulty striking a reasonable balance between high throughput and low hardware consumption. In this paper, a novel lightweight high-throughput TRNG based on state switchable ring oscillators (SSROs) is proposed. Under the effect of flip-flops that are prone to entering the metastable region, the SSROs randomly switch between oscillatory and buffer states to create jitter and metastability. A feedback strategy is adopted to effectively eliminate the fixed point in the circuit, which further enhances the randomness of the structure. The proposed TRNG is implemented on Xilinx Artix-7 and Kintex-7 FPGAs, with support for automatic routing. It achieves a throughput of up to 400 Mbps while consuming only 16 LUTs and 13 DFFs, showing extremely high resource utilization efficiency. Experimental results show that the output random sequence passes the NIST SP800-22 test, the NIST SP800-90B test, and the AIS-31 test without any post-processing, exhibiting strong robustness against voltage and temperature variations as well as frequency injection attacks.

Hetero dielectric based dual material gate AlGaN channel MISHEMT for enhanced electrical characteristics

Herein, we report an AlGaN channel metal insulator semiconductor high electron mobility transistor (MISHEMT) in dual material gate (DMG) architecture with two different dielectrics as gate insulator for enhancing the DC performance of the device. The use of a high-k dielectric material as gate insulator below gate metal 1 and a low-k dielectric below gate metal 2 results in significant threshold voltage variation along the channel. This contributes to improved average carrier velocity which in turn results in better current drive. The proposed device exhibits a peak current of 162 mA/mm at zero gate bias, whereas, the DMG and single material gate (SMG) AlGaN channel HEMTs offer currents of 137 mA/mm and 125 mA/mm respectively. The peak transconductances are about 24.66 mS/mm, 23.68 mS/mm and 22.71 mS/mm respectively for the proposed device, DMG and SMG HEMTs. The proposed device reduces the OFF current by an order of 106 compared to that of DMG HEMT.

High-Temperature Characterization of AlGaN Channel High Electron Mobility Transistor Based on Silicon Substrate

In this paper, it is demonstrated that the AlGaN high electron mobility transistor (HEMT) based on silicon wafer exhibits excellent high-temperature performance. First, the output characteristics show that the ratio of on-resistance (RON) only reaches 1.55 when the working temperature increases from 25 °C to 150 °C. This increase in RON is caused by a reduction in optical phonon scattering-limited mobility (μOP) in the AlGaN material. Moreover, the device also displays great high-performance stability in that the variation of the threshold voltage (ΔVTH) is only 0.1 V, and the off-state leakage current (ID,off-state) is simply increased from 2.87 × 10−5 to 1.85 × 10−4 mA/mm, under the operating temperature variation from 25 °C to 200 °C. It is found that the two trap states are induced at high temperatures, and the trap state densities (DT) of 4.09 × 1012~5.95 × 1012 and 7.58 × 1012~1.53 × 1013 cm−2 eV−1 are located at ET in a range of 0.46~0.48 eV and 0.57~0.61 eV, respectively, which lead to the slight performance degeneration of AlGaN HEMT. Therefore, this work provides experimental and theoretical evidence of AlGaN HEMT for high-temperature applications, pushing the development of ultra-wide gap semiconductors greatly.

Exploring LGE areas in the atria: Insights from electroanatomical voltage mapping in AF patients

Abstract Introduction Late gadolinium enhancement MRI (LGE MRI) is a common method for the evaluation of the atrial substrate in atrial fibrillation (AF) patients. The extent of LGE is associated with atrial cardiomyopathy and ablation outcomes. However, previous studies have yielded inconsistent results in detecting low voltage areas (LVA) using bipolar electroanatomical mapping (EAM) in LGE regions. Objective Conduct a thorough analysis of the bipolar and unipolar voltage in LGE areas and its relationship with the voltage in non-LGE areas, utilizing high-density (HD) EAM generated by a multipolar HD-mapping catheter. Methods In this study, 20 patients undergoing AF ablation were examined using LGE-MRI. A 3D mesh integrating LGE data was generated. HD-EAM (> 4000 points) was performed in sinus rhythm. The EAM map and MRI mesh underwent manual alignment and registration. Using a nearest neighbor algorithm, EAM points nearest to LGE areas were identified, and the corresponding unipolar and bipolar voltage values, along with LGE voxel intensity, were exported for analysis. Results LGE areas exhibited a median bipolar voltage amplitude of 0.93 mV, median unipolar voltage of 1.73 mV. In contrast, areas without enhancement displayed median bipolar voltage of 2.33 mV, unipolar voltage of 3.58 mV. We observed a variation in voltage amplitudes across the different LGE areas: bipolar voltage ranged from 0.04 to 2.51 mV and unipolar voltage from 0.22 to 3.75 mV. This variation strongly correlated with voxel intensity in LGE areas (correlation coefficient r = -0.86 [p <0.001]). Irrespective of the voltage amplitude in the examined LGE areas, a significant voltage drop was observed, with an average reduction of 54% in bipolar and 51% in unipolar voltages, compared to the amplitudes in non-LGE areas within the same atria. Conclusion Variations in bipolar and unipolar voltage within LGE areas are significantly correlated with local voxel intensity. Despite the inconsistent overlap with the predefined bipolar threshold for LVA, LGE regions exhibit a pronounced and consistent reduction in both bipolar and unipolar voltage compared to non-LGE areas. This pattern suggests notable electrophysiological changes in these areas. These insights underscore the need for further investigation to better understand the implications and mechanisms underlying these alterations in LGE regions.

Chemical Bath Deposition of NiFe Alloy Anode for Efficient Alkaline Water Electrolyzer Integration.

Green hydrogen production from water splitting is a feasible way for intermittent renewable energy storage and utilization, where the exploration and scale-up preparation of high-performance anodic oxygen evolution electrocatalysts are critical prerequisites for its industrial-level applications. Herein, a chemical bath deposition of FeNi3 intermetallic alloys onto Ni mesh support is performed, which delivers a current density of 0.62 Acm-2 at 1.72 V versus reversible hydrogen electrode for alkaline water oxidation in 1 m KOH and an excellent electrolysis stability at 0.2 A cm-2 for over 300 h. Moreover, via 3D computational fluid dynamics simulation and flow field optimization, a homogeneous deposition of ≈5400 cm2 NiFe anode is demonstrated within 4 min using the developed flow bath reactor. Once integrating the as-prepared NiFe anodes into alkaline electrolyzer stack, the voltage variation between each unit cell is below 40 mV at a total operation current of 71 A, or ca. current density of 0.2 A cm-2, confirming the uniformity of this batch synthesis protocol and its great potential for industrial alkaline water electrolysis.

Early Internal Short Circuit Diagnosis for Lithium-Ion Battery Packs Based on Dynamic Time Warping of Incremental Capacity

Timely identification of early internal short circuit faults, commonly referred to as micro short circuits (MSCs), is essential yet poses significant challenges for the safe and reliable operation of lithium-ion battery (LIB) energy storage systems. This paper introduces an innovative diagnostic method for early internal short circuits in LIB packs, utilizing dynamic time warping (DTW) applied to incremental capacity (IC). Initially, the terminal voltages of all cells within the LIB pack are ordered at any moment to determine the median terminal voltage, which is then used to generate the median IC curve. This curve acts as a reference benchmark that represents the condition of healthy cells in the pack. Subsequently, the DTW algorithm is utilized to measure the similarity between each cell’s IC curve and the median IC curve. Cells exhibiting similarity scores that exceed a specified threshold are identified as having MSC faults. Lastly, for the cells diagnosed with MSC conditions, a method for estimating short-circuit resistance (SR) based on variations in maximum charging voltage is devised to quantitatively evaluate the severity and evolution of the MSC. Experimental findings reveal that the proposed method effectively identifies MSC cells in the LIB pack and estimates their SRs without the necessity of a battery model, thereby affirming the method’s validity.

The Effect of Tube Voltage Variations on CT Scan Image Quality at Prof. I G. N. G. Ngoerah General Hospital, Denpasar, Indonesia

Aims: Knowing the SNR and CNR values obtained from the image results that have been varied in the tube voltage. Knowing the effect of variations in the tube voltage value on the quality of the CT scan image that will be produced. Place and Duration of Study: Radiology installation of Prof. I G. N. G. Ngoerah General Hospital, Denpasar from May 2024 to August 2024. Methodology: This study used a Canon Aquilion LB CT Scanner to scan a TOS phantom containing 6 materials (polypropylene, nylon, acrylic, derlin, air, and water) with varying tube voltages (80 kV, 100 kV, 120 kV, 135 kV). The data were analyzed using PSPP and Excel to calculate SNR and CNR, and statistical tests for normality, Pearson correlation, and simple regression were performed. Results: The image data analyzed includes the average value of the object ROI, the average ROI background, and the standard deviation of the background. The data is grouped based on the variation of the tube voltage, the average value and standard deviation of the ROI on each material, and the standard deviation of the background. The results obtained for the relationship between the variation of the tube voltage and the SNR value are that the tube voltage affects the SNR value by 94,02% in polypropylene, 97,79% in nylon, 97,71% in acrylic, 96,42% in derlin, and 94,22% in air. And for the relationship between the tube voltage and the CNR value, the tube voltage affects the CNR value by 93,65% in polypropylene, 97,35% in nylon, 96,81% in acrylic, 95,62% in derlin, and 94,65% in air. Conclusion: Selecting the right tube voltage is important to optimize CT scan image quality, with 120 kV and 135 kV recommended for organs such as the kidney, liver, and lungs as they produce better SNR and CNR. Organs with significant attenuation differences show increased SNR and CNR, while soft tissues such as fat experience decreased contrast at high voltages. The use of tube voltage must be adjusted to diagnostic needs and evaluated through quality control according to BAPETEN regulation Number 2 of 2018.

The relationship of voltage variations in the third quadrant and the Schottky area ratios in a 4H-SiC SBD-embedded MOSFET

Based on the measured and the TCAD simulation results, this paper provides a detailed description of the third quadrant characteristics of the Schottky barrier diode (SBD) embedded MOSFETs with different Schottky area ratios of 2.6 %, 5.3 %, and 14.7 %. As the Schottky area ratio increases, the shift of the third quadrant turn-on voltages of the MOSFETs influenced by the gate voltage decreases. The shift rates in the conventional MOSFET and SBD-embedded MOSFETs are from 57.2 % to 0 % when Vgs changes from 0 V to −4 V. The shift rate becomes 0 % when the Schottky area ratio is larger than 5.3 %. Simultaneously, the TCAD simulation results and the measured results indicate that the SBD-embedded MOSFETs can effectively suppress the conduction of the low barrier diode and the body diode.Furthermore, the SPICE models were built to explain the physics mechanisms. The fitting error between the measured and fitting results is as low as 1.3 % among the models with the different Schottky area ratios.