Current Pulses Research Articles

Field tests of square and double exponential pulses for transient resistivity measurements using Wenner arrays and hemispheres

Models of frequency-dependent soil resistivity ρ(f) suggest the dual concept of time-dependent resistivity ρ(t) that, for high resistivity soil, increases from 100 ns to 100 μs, a range of time relevant for lightning backflashover performance calculations. Measurements of ρ(t) can be made by impressing impulse or step current and monitoring voltage rise. Time-dependent resistivity can be established with Wenner or Schlumberger probe arrays and also with oblique fall-of-potential measurements from buried hemispheres. Tests show that rectangular and double-exponential pulse currents both have value. Specialized evaluation using “Drained Net Charge” concepts may yield estimates of low-frequency resistivity ρo.

Internal temperature estimation for lithium-ion batteries through distributed equivalent circuit network model

Lithium-ion cells experience significant internal thermal gradients during operation, with a direct impact on their safety, performance, cost and lifetime. The estimation of the internal temperature of cells is therefore particularly important. In this work, a 3D distributed electro-thermal model for internal temperature estimation is developed for a cylindrical cell (LG M50T, NMC811). The model is parameterized and comprehensively validated against experimental data for 21700 cells, including direct core temperature measurements. Multiple types of electrical load are considered, including constant current discharge, pulse discharge, drive cycle and instant discharge/charge switching. The developed model is used to estimate core temperature based on surface temperature measurement. The predictions are shown to have good accuracy at relatively low computational cost. We show that the widely adopted two-node lumped thermal estimation model is increasingly inaccurate for more aggressive discharges, when thermal gradients become higher. Compared to the standard two-node model, the distributed equivalent circuit network model predicts the effects of detailed internal cell structure (electrode, current collector, metal can and tab) and distributed internal heat generation. The results are of immediate interest to cell manufacturers and battery pack designers, while the modelling and parameterization framework is a useful tool for energy storage systems design.

PMSNet: Multiscale Partial-Discharge Signal Feature Recognition Model via a Spatial Interaction Attention Mechanism

Partial discharge (PD) is a localized discharge phenomenon in the insulator of electrical equipment resulting from the electric field strength exceeding the local dielectric breakdown electric field. Partial-discharge signal identification is an important means of assessing the insulation status of electrical equipment and critical to the safe operation of electrical equipment. The identification effect of traditional methods is not ideal because the PD signal collected is subject to strong noise interference. To overcome noise interference, quickly and accurately identify PD signals, and eliminate potential safety hazards, this study proposes a PD signal identification method based on multiscale feature fusion. The method improves identification efficiency through the multiscale feature fusion and feature aggregation of phase-resolved partial-discharge (PRPD) diagrams by using PMSNet. The whole network consists of three parts: a CNN backbone composed of a multiscale feature fusion pyramid, a down-sampling feature enhancement (DSFB) module for each layer of the pyramid to acquire features from different layers, a Transformer encoder module dominated by a spatial interaction–attention mechanism to enhance subspace feature interactions, a final categorized feature recognition method for the PRPD maps and a final classification feature generation module (F-Collect). PMSNet improves recognition accuracy by 10% compared with traditional high-frequency current detection methods and current pulse detection methods. On the PRPD dataset, the validation accuracy of PMSNet is above 80%, the validation loss is about 0.3%, and the training accuracy exceeds 85%. Experimental results show that the use of PMSNet can greatly improve the recognition accuracy and robustness of PD signals and has good practicality and application prospects.

Parametric analysis, modeling and optimization of the process parameters in electric discharge machining of aluminium metal matrix composite

Optimizing electric discharge machining (EDM) for aluminum/SiCp metal matrix composites poses challenges due to intricate machine parameters and process complexity, impacting process economy and elevating product costs. The research aims to find the optimal combination of process parameters which include pulse on-time, pulse current, duty cycle (%), gap voltage, sensitivity and flushing pressure for EDM of Al/SiCp-MMC using a copper electrode for the selected response factors such as material erosion rate and surface roughness, Ra. The experiments were designed using the central composite design of response surface methodology and an advanced optimization technique known as Teaching–learning-based optimization (TLBO), is applied to find the optimal combination of process parameters to obtain maximum material erosion rate subject to the desired range of surface roughness (SR), Ra. The combination of the high pulse on-time (i.e. 150 μs) and high pulse current (i.e. 12A) results in high material removal rate with deep craters on the machined surface clearly visible in SEM images contrasting the minimized surface roughness at lower values of pulse on-time (50 μs) and the pulse current (4A). Pulse on - time (Ton) is found to be the most significant factor for material erosion rate and surface roughness with percentage contribution of 70.86 and 54.9 respectively for optimization of the response. The regression models were developed at 95% confidence level for material removal rate and surface roughness with R2 value of 0.93 and 0.95 respectively signifying high degree of accuracy in predicting the response. Confirmation tests conducted to check the adequacy of the established models revealed that the percentage error between the predicted and experimental responses is found to be within acceptable levels. Electron discharge machining of the aluminium metal matrix composite at the optimized conditions could provide economical aspect in the aerospace and automobile industry.

Single current control of magnetization in vertical high-aspect-ratio nanopillars on in-plane magnetization layers

Ferromagnetic pillars standing on a substrate hold promise for use in recording segments of multibit nonvolatile memories. These pillars exhibit high thermal stability in their magnetization owing to the influence of shape and perpendicular magnetic anisotropies. Recent micromagnetic simulations have demonstrated the feasibility of magnetization control in these pillars. Such control was achieved through the spin-transfer torque induced by the current flowing within the pillar and the spin-orbit torque generated by the current flowing through the heavy-metal lead at the bottom of the pillars. However, the presence of two current paths complicates circuit design, posing challenges in device integration. To solve this problem, we propose a new structure wherein a pillar is placed on a thin film with in-plane magnetization. When current flows through this structure, a torque is applied to the magnetization of the pillar, similar to that of the three-terminal structure. Magnetization reversal and control in the proposed structure were demonstrated using micromagnetic simulations. Specifically, magnetization reversal was achieved in a 100 nm-long permalloy pillar, whereas the magnetization corresponding to a three-bit sequence was generated in a 250 nm-long permalloy pillar. We propose two methods to control the magnetization of multibit memory. One method uses two different current intensities, whereas the other uses constant and pulsed currents of identical intensity. Notably, in the proposed structure, magnetization was controlled using only a unidirectional current. In particular, magnetization can be controlled with a pulsed current using a single current strength. This advancement will simplify the circuitry required to control magnetic memory, bringing the realization of magnetic memory devices closer to reality.

POWER FACTOR IMPROVEMENT BY USING STATIC VARIABLE COMPENSATOR

This project aims to improve the power factor of transmission lines using a static variable compensator. Traditional methods using large rotating parts were inefficient and prone to damage. Static VAR Compensation under FACTS employs Thyristor Switched Capacitors (TSC) controlled by a programmed microcontroller. This system compensates the power factor using thyristor-switched capacitors, where the zero voltage and zero current pulses are fed to a microcontroller. Previously, power factor compensation relied on large machines like synchronous condensers or switched capacitor banks. Shunt capacitive compensation, where a shunt capacitor is connected to draw current leading the source voltage, improves the power factor for inductive loads. The program controls opto-isolators interfaced with SCRs to achieve near-unity power factor. The project can be further enhanced with thyristor-controlled triggering for precise power factor correction.

Strengthening and Toughening of ZG25SiMn2CrB Steel without Tempering Brittleness via Electropulsing Treatment

High-strength low-alloy steels are widely used, but their traditional heat-treatment process is complex, energy-intensive, and makes it difficult to fully exploit the material’s potential. In this paper, the electropulsing processing technology was applied to the quenching and tempering process of ZG25SiMn2CrB steel. Through microstructural characterization and mechanical property testing, the influence of electropulsing on the solid-state phase transition process of annealing steel was systematically studied. The heating process of the specimen with the annealing state (initial state) is the diffusion-type transition. As the discharge time increased, the microstructure gradually transformed from ferrite/pearlitic to slate martensite. Optimal mechanical properties and fine microstructure were achieved after quenching at 500 ms. The steel subjected to rapid tempering with 160 ms electropulsing exhibited good, comprehensive mechanical properties (tensile strength 1609 MPa, yield strength 1401.27 MPa, elongation 11.63%, and hardness 48.68 HRC). These favorable mechanical properties are attributed to the coupled impact of thermal and non-thermal effects induced by high-density pulse current. Specifically, the thermal effect provides the thermodynamic conditions for phase transformation, while the non-thermal effect reduces the nucleation barrier of austenite, which increases the nucleation rate during instantaneous heating, and the following rapid cooling suppresses the growth of austenite grains. Additionally, the fine microstructure prevents the occurrence of temper brittleness.

Antiferromagnetic magnonic charge current generation via ultrafast optical excitation

Néel spin-orbit torque allows a charge current pulse to efficiently manipulate the Néel vector in antiferromagnets, which offers a unique opportunity for ultrahigh density information storage with high speed. However, the reciprocal process of Néel spin-orbit torque, the generation of ultrafast charge current in antiferromagnets has not been demonstrated. Here, we show the experimental observation of charge current generation in antiferromagnetic metallic Mn2Au thin films using ultrafast optical excitation. The ultrafast laser pulse excites antiferromagnetic magnons, resulting in instantaneous non-equilibrium spin polarization at the antiferromagnetic spin sublattices with broken spatial symmetry. Then the charge current is generated directly via spin-orbit fields at the two sublattices, which is termed as the reciprocal phenomenon of Néel spin-orbit torque, and the associated THz emission can be detected at room temperature. Besides the fundamental significance on the Onsager reciprocity, the observed magnonic charge current generation in antiferromagnet would advance the development of antiferromagnetic THz emitter.

Microstructure Characteristics and Mechanical Properties of γ-TiAl/Steel Joints with Different Laser Pulse Currents

Microstructure Characteristics and Mechanical Properties of γ-TiAl/Steel Joints with Different Laser Pulse Currents

Artificial Neuron Based on the Bloch-Point Domain Wall in Ferromagnetic Nanowires.

Nanomagnetism and spintronics are currently active areas of research, with one of the main goals being the creation of low-energy-consuming magnetic memories based on nanomagnet switching. These types of devices could also be implemented in neuromorphic computing by crafting artificial neurons (ANs) that emulate the characteristics of biological neurons through the implementation of neuron models such as the widely used leaky integrate-and-fire (LIF) with a refractory period. In this study, we have carried out numerical simulations of a 120 nm diameter, 250 nm length ferromagnetic nanowire (NW) with the aim of exploring the design of an artificial neuron based on the creation and destruction of a Bloch-point domain wall. To replicate signal integration, we applied pulsed trains of spin currents to the opposite faces of the ferromagnetic NW. These pulsed currents (previously studied only in the continuous form) are responsible for inducing transitions between the stable single vortex (SV) state and the metastable Bloch point domain wall (BP-DW) state. To ensure the system exhibits leak and refractory properties, the NW was placed in a homogeneous magnetic field of the order of mT in the axial direction. The suggested configuration fulfills the requirements and characteristics of a biological neuron, potentially leading to the future creation of artificial neural networks (ANNs) based on reversible changes in the topology of magnetic NWs.

Dynamic Manipulation of Chiral Domain Wall Spacing for Advanced Spintronic Memory and Logic Devices.

Nanoscopic magnetic domain walls (DWs), via their absence or presence, enable highly interesting binary data bits. The current-controlled, high-speed, synchronous motion of sequences of chiral DWs in magnetic nanoconduits induced by current pulses makes possible high-performance spintronic memory and logic devices. The closer the spacing between neighboring DWs in an individual conduit or nanowire, the higher the data density of the device, but at the same time, the more difficult it is to read the bits. Here, we show how the DW spacing can be dynamically varied to facilitate reading for otherwise closely packed bits. In the first method, the current density is increased in portions of the conduit that, thereby, locally speeds up the DWs, decompressing them and making them easier to read. In the second method, a localized bias current is used to compress and decompress the DW spacing. Both of these methods are demonstrated experimentally and validated by micromagnetic simulations. DW compression and decompression rates as high as 88% are shown. These methods can increase the density with which DWs can be packed in future DW-based spintronic devices by more than an order of magnitude.

Study of the microstructure evolution of alloy structural steel and inhomogeneity effect of the microscale pulsed currents during current-assisted plane strain compressions by modeling a novel cellular automata method

The current-assisted forming process is considered to be a novel process that utilizes the electroplasticity effect to reduce the deformation resistance of difficult-to-deform metals and to refine the grain size while improving the mechanical properties of the part. However, the lack of understanding of the mechanisms by which pulsed current affects grain refinement still makes it difficult to experimentally develop analytical or empirical models of the relationship between grain size, pulse current parameters, and deformation amount. It will seriously hinder the further development and application of the current-assisted forming process. To reveal the mechanism of grain refinement coupling with electroplasticity, a series of Electron Back Scattering Diffraction observation tests were carried out after current-assisted plane strain compressions. The results show that the grain orientation spread value of the pulse current condition is lower than that of the non-current condition, while the refined grain area percentage is higher than that of the non-current condition. Based on the microstructure observation results, a cellular automata model for grain refinement is proposed. This consists of a dislocation density evolution, sub-grains generation, grain fragmentation, and a grain orientation rotation algorithm. To study the electroplasticity of the grain refinement process, the cellular automata model is also embedded with a finite difference numerical algorithm for solving the microscopic current density distribution of the model. The cellular automata model simulation results show that the error of grain size accuracy of this cellular automata model under non-current and pulse current conditions is 10.48% and 8.55%, respectively. It shows that the model can accurately characterize the grain refinement behavior of the current-assisted plane strain compression. The simulation results reveal the deep mechanism of pulsed current promotion on grain refinement, i.e., an inhomogeneous microstructure leads to uneven distribution of pulse current density. The inhomogeneous current distribution will further increase the grain refinement rate in the coarse-grained regions, thus increasing the proportion of the refined grain regions in the microstructure and leading to a relatively more homogeneous microstructure under pulse current conditions. The cellular automata model accurately reveals the mechanism of electroplasticity on the grain refinement. The model will serve as a crucial theoretical reference in designing current-assisted forming process routes to ensure excellent microstructure and properties in manufactured parts. It will enhance the widespread utilization of current-assisted forming process.

Pulsed current-assisted twelve-roll precision rolling deformation of SUS304 ultra-thin strips with exceptional mechanical properties

Innovative pulsed current-assisted multi-pass rolling tests were conducted on a 12-roll mill during the rolling deformation processing of SUS304 ultra-thin strips. The results show that in the first rolling pass, the rolling reduction rate of a conventionally rolled sample (at room temperature) is 33.8%, which can be increased to 41.5% by pulsed current-assisted rolling, enabling the formation of an ultra-thin strip with a size of 67.3 μm in only one rolling pass. After three passes of pulsed current-assisted rolling, the thickness of the ultra-thin strip can be further reduced to 51.7 μm. To clearly compare the effects of a pulsed current on the microstructure and mechanical response of the ultra-thin strip, ultra-thin strips with nearly the same thickness reduction were analyzed. It was found that pulsed current can reduce the degree of work-hardening of the rolled samples by promoting dislocation detachment, reducing the density of stacking faults, inhibiting martensitic phase transformation, and shortening the total length of grain boundaries. As a result, the ductility of ultra-thin strips can be effectively restored to approximately 16.3% while maintaining a high tensile strength of 1118 MPa.Therefore, pulsed current-assisted rolling deformation shows great potential for the formation of ultra-thin strips with a combination of high strength and ductility.

Quantized non-volatile nanomagnetic domain wall synapse based autoencoder for efficient unsupervised network anomaly detection

Abstract Anomaly detection in real-time using autoencoders implemented on edge devices is exceedingly challenging due to limited hardware, energy, and computational resources. We show that these limitations can be addressed by designing an autoencoder with low-resolution non-volatile memory-based synapses and employing an effective quantized neural network learning algorithm. We further propose nanoscale ferromagnetic racetracks with engineered notches hosting magnetic domain walls (DW) as exemplary non-volatile memory based autoencoder synapses, where limited state (5-state) synaptic weights are manipulated by spin orbit torque (SOT) current pulses to write different magnetoresistance states. The performance of anomaly detection of the proposed autoencoder model is evaluated on the NSL-KDD dataset. Limited resolution and DW device stochasticity aware training of the autoencoder is performed, which yields comparable anomaly detection performance to the autoencoder having floating-point precision weights. While the limited number of quantized states and the inherent stochastic nature of DW synaptic weights in nanoscale devices are typically known to negatively impact the performance, our hardware-aware training algorithm is shown to leverage these imperfect device characteristics to generate an improvement in anomaly detection accuracy (90.98%) compared to accuracy obtained with floating-point synaptic weights that are extremely memory intensive. Furthermore, our DW-based approach demonstrates a remarkable reduction of at least three orders of magnitude in weight updates during training compared to the floating-point approach, implying significant reduction in operation energy for our method. This work could stimulate the development of extremely energy efficient non-volatile multi-state synapse-based processors that can perform real-time training and inference on the edge with unsupervised data.

Selective intrafascicular stimulation of myelinated and unmyelinated nerve fibers through a longitudinal electrode: A computational study

Carbon nanotube (CNT) fiber electrodes have demonstrated exceptional spatial selectivity and sustained reliability in the context of intrafascicular electrical stimulation, as evidenced through rigorous animal experimentation. A significant presence of unmyelinated C fibers, known to induce uncomfortable somatosensory experiences, exists within peripheral nerves. This presence poses a considerable challenge to the excitation of myelinated Aβ fibers, which are crucial for tactile sensation. To achieve nuanced tactile sensory feedback utilizing CNT fiber electrodes, the selective stimulation of Aβ sensory afferents emerges as a critical factor.In confronting this challenge, the present investigation sought to refine and apply a rat sciatic-nerve model leveraging the capabilities of the COMSOL-NEURON framework. This approach enables a systematic evaluation of the influence exerted by stimulation parameters and electrode geometry on the activation dynamics of both myelinated Aβ and unmyelinated C fibers. The findings advocate for the utilization of current pulses featuring a pulse width of 600 μs, alongside the deployment of CNT fibers characterized by a diminutive diameter of 10 μm, with an exclusively exposed cross-sectional area, to facilitate reduced activation current thresholds. Comparative analysis under monopolar and bipolar electrical stimulation conditions revealed proximate activation thresholds, albeit with bipolar stimulation exhibiting superior fiber selectivity relative to its monopolar counterpart. Concerning pulse waveform characteristics, the adoption of an anodic-first biphasic stimulation modality is favored, taking into account the dual criteria of activation threshold and fiber selectivity optimization. Consequently, this investigation furnishes an efficacious stimulation paradigm for the selective activation of touch-related nerve fibers, alongside provisioning a comprehensive theoretical foundation for the realization of natural tactile feedback within the domain of prosthetic hand applications.

Maskless photolithography based on ultraviolet micro-LEDs and direct writing method for improving pattern resolution

Ultraviolet micro-LEDs show great potential as a light source for maskless photolithography. However, there are few reports on micro-LED based maskless photolithography systems, and the studies on the effects of system parameters on exposure patterns are still lacking. Hence, we developed a maskless photolithography system that employs micro-LEDs with peak wavelength 375 nm to produce micrometer-sized exposure patterns in photoresists. We also systematically explored the effects of exposure time and current density of micro-LED on static direct writing patterns, as well as the effects of stage velocity and current pulse width on dynamic direct writing patterns. Furthermore, reducing the size of micro-LED pixels enables obtaining high-resolution exposure patterns, but this approach will bring technical challenges and high costs. Therefore, this paper proposes an oblique direct writing method that, instead of reducing the micro-LED pixel size, improves the pattern resolution by changing the tilt angle of the sample. The experimental results show that the linewidths of the exposed lines decreased by 4.0% and 15.2%, respectively, as the sample tilt angle increased from 0° to 15° and 30°, which confirms the feasibility of the proposed method to improve the pattern resolution. This method is also expected to correct the exposure pattern error caused by optical distortion of the lens in the photolithography system. The system and method reported can be applied in various fields such as PCBs, photovoltaics, solar cells, and MEMS.

Experimental study of the influence of O2 content on electrical and optical characteristics of He/CF4 APPJ

CF4 is an important source of reactive F-containing species (RFS) so that it is used to mix with inert gas as the working gas of atmospheric pressure plasma jet (APPJ) for material surface fluoridation modification. The addition of a small amount of O2 can increase the density of RFS in He/CF4 APPJ. Therefore, the hydrodynamic, electrical and optical properties of He/CF4/O2 APPJ interacting with the dielectric are experimentally investigated in this paper. Meanwhile, the influence of the excitation source on plasma discharge is discussed in detail and the internal mechanism of the experimental phenomenon in this paper is analyzed using the simulation results based on the model established in the previous paper. It is found that the addition of a small amount of O2 can increase the intensity and accelerate the axial propagation speed of He/CF4 APPJ due to the low ionization energy of O2 and the increase of the Penning ionization between metastable He and O2. With the increase of O2 content, the stability of the discharge is gradually enhanced due to the electron attachment reaction of O2 and the position of the primary current pulse in each half voltage cycle gradually approaches the position of the peak voltage because the increase in O2 content raises the breakdown threshold in dielectric barrier discharge region. In the presence of downstream dielectric, the addition of 0.1%O2 does not significantly change the radial development radius of APPJ due to the higher electron attachment rate and electron collision excitation loss power. The discharge pulse intensity is generally reduced compared to the absence of dielectric and the glow discharge in the strict sense no longer exists. The continuous spectrum intensity of RFS increases with the addition of a small amount of O2 while decreases significantly when O2 content is too high.

State of Health Estimation for Lithium-Ion Battery Based on Sample Transfer Learning under Current Pulse Test

Considering the diversity of battery data under dynamic test conditions, the stability of battery working data is affected due to the diversity of charge and discharge rates, variability of operating temperature, and randomness of the current state of charge, and the data types are multi-sourced, which increases the difficulty of estimating battery SOH based on data-driven methods. In this paper, a lithium-ion battery state of health estimation method with sample transfer learning under dynamic test conditions is proposed. Through the Tradaboost.R2 method, the weight of the source domain sample data is adjusted to complete the update of the sample data distribution. At the same time, considering the division methods of the six auxiliary and the source domain data set, aging features from different state of charge ranges are selected. It is verified that while the aging feature dimension and the demand for target domain label data are reduced, the estimation accuracy of the lithium-ion battery state of health is not affected by the initial value of the state of charge. By considering the mean absolute error, mean square error and root mean square error, the estimated error results do not exceed 1.2% on the experiment battery data, which highlights the advantages of the proposed methods.

Self-pulsing of dielectric barrier discharges at low driving frequencies

This paper investigates the self-pulsing of dielectric barrier discharges (DBDs) at low driving frequencies. In particular, (a) the dependence of current on the product pd of gas pressure p and the gas gap length d, (b) the effects of lossy dielectrics (in resistive discharges) and large dielectric permittivity (in ferroelectrics) on current dynamics, (c) the transition from Townsend to a dynamic capacitively coupled plasma (CCP) discharge with changing pd values, and (d) the transition from Townsend to a high-frequency CCP regime with increasing the driving frequency. A one-dimensional fluid model of argon plasma is coupled to an equivalent RC circuit for lossy dielectrics. Our results show multiple current pulses per AC period in Townsend and CCP discharge modes which are explained by uncoupled electron–ion transport in the absence of quasineutrality and surface charge deposition at dielectric interfaces. The number of current pulses decreases with an increasing applied frequency when the Townsend discharge transforms into the CCP discharge. The resistive barrier discharge with lossy dielectrics exhibits Townsend and glow modes for the same pd value (7.6 Torr cm) for higher and lower resistances, respectively. Finally, we show that ferroelectric materials can amplify discharge current in DBDs. Similarities between current pulsing in DBD, Trichel pulses in corona discharges, and subnormal oscillations in DC discharges are discussed.

Transient turn-on characteristics of Si RBDT and SiC MOSFET under nanosecond current pulse range

With the development of pulse power supplies, solid-state semiconductor switches are required to have fast switching speeds and low losses. Both Reverse blocking diode thyristor (RBDT) and silicon carbide metal oxide semiconductor field effect transistor (SiC MOSFET) have fast turn-on speed, making them suitable candidates for short pulse generator. In this paper, the transient turn-on characteristics of Si RBDT and SiC MOSFET are analyzed theoretically and validated experimentally. Si RBDT and commercial 1.2 kV/81A SiC MOSFET are comparatively investigated in switching current pulse with a rise time of several hundreds of nanoseconds. (1) The anode current of RBDT could rise exponentially because of the latch-up effect of Si RBDT, while the drain current of SiC MOSFET tends to be saturated. (2) Utilizing the current rise time (Trise) to represent the switching speed, SiC MOSFET can switch faster when the current is lower than 400A. With the increase of the current, Si RBDT presents faster turn-on speed and lower switching loss due to the regenerative action of the two coupled transistors. (3) The transient characteristics of Si RBDT include a voltage-controlled inductance, while SiC MOSFET contains a current-controlled inductance based on the current rise time, respectively. With the increasing of the main voltage, the equivalent inductance of Si RBDT decreases and tends to be saturated when the main voltage is higher than half of the breakdown voltage of Si RBDT. For SiC MOSFET, the equivalent inductance increases until the drain current remains stable for a given gate voltage. This paper confirms the advantages of Si RBDT and SiC MOSFET in different situations.