Datasheet-Driven Compact Model of Silicon Carbide Power MOSFET Including Third-Quadrant Behavior

Rashid, Arman Ur; Hossain, Maksudul; Emon, Asif Imran; Mantooth, H. Alan

doi:10.1109/tpel.2021.3062737

Cited by 24 publications

(30 citation statements)

References 24 publications

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“…The switching behavior of the SiC MOSFET is directly related to the reliability of the device (Chen et al, 2021;Rashid et al, 2021). Therefore, it is important to carry out the comprehensive research about the influence of driving parameters and parasitic parameters on the switching behaviors of the SiC MOSFET.…”

Section: Switching Behaviorsmentioning

confidence: 99%

Influence of driving and parasitic parameters on the switching behaviors of the SiC MOSFET

Zhang

2023

Front. Energy Res.

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The SiC MOSFET has lower conduction loss and switching loss than the Si IGBT, which helps to improve the efficiency and power density of the converter, especially for those having strict requirements for volume and weight, for example, electrical vehicles (EVs), on-board chargers (OBCs), and traction drive systems (TDS). However, the faster switching speed will cause overshoot and oscillation problems, which will affect the efficiency and security of the SiC devices and power electronic systems. For the SiC MOSFET to be better used, combining a theoretical analysis, the double-pulse test platform is built. The controllable principles of SiC MOSFETs are validated. The turn-on and turn-off delay, switching delay, switching di/dt, switching du/dt, switching overshoot, and switching loss of SiC MOSFETs under different driving and parasitic parameters are explored. Finally, some valuable suggestions for designing are proposed for a better application of the SiC MOSFET.

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Section: Switching Behaviorsmentioning

confidence: 99%

Influence of driving and parasitic parameters on the switching behaviors of the SiC MOSFET

Zhang

2023

Front. Energy Res.

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“…It can provide more excellent switching characteristics and lower on-state voltage drop compared with the Si-based power devices [17]. More importantly, the reverse recovery loss generated by the SiC-SBD is almost negligible [18]. Therefore, based on the power module configuration, the developed LUT-based electro-thermal model, whose block diagram is depicted in Fig.…”

Section: Lut-based Electro-thermal Modeling Of Os-ibcmentioning

confidence: 99%

Lookup Table-based Electro-Thermal Real-Time Simulation of Output Series Interleaved Boost Converter for Fuel Cell Applications

Bai

Breaz

et al. 2021

IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society

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Due to the high dependency between reliability of power device and its junction temperature, monitoring their thermal behavior in real time is very essential. In this paper, a lookup table-based electro-thermal real-time simulation model is developed to quickly estimate the junction temperature of the power devices. Output series interleaved boost converter with high voltage gain and low input current ripple, which is dedicated for fuel cell application, is selected as a case study. The thorough design and implementation process are presented and the developed model is simulated with a 200 nanoseconds time step on NI FlexRIO PXIe-7975R real-time platform. Moreover, the effectiveness and accuracy of the FPGA-based electrothermal model are validated by comparison the results from PLECS software.

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“…Instead, behavior models are widely used in transient circuit simulation due to their simplicity and fast computation speed [17], which is therefore the focus of this paper. Most existing behavior models are implemented using mathematical equations to match the measured device characteristics, such as I-V and C-V characteristics [18]. Complex nonlinear equations are firstly designed according to the device characteristics.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Data-Driven Modeling Methodology for Fast and Accurate Transient Simulation of SiC MOSFETs

Yang

Ming

Liang

et al. 2022

IEEE Trans. Power Electron.

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To enable fast and accurate models of SiC MOS-FETs for transient simulation, a hybrid data-driven modeling methodology of SiC MOSFETs is proposed. Unlike conventional modeling methods that are based on complex nonlinear equations, data-driven Artificial Neural Networks (ANNs) are used in this paper. For model accuracy, the I-V characteristics are measured in the whole operation region to train the ANN. The ANN model is then combined with behavior-based equations to model the cutoff region and to avoid overfitting the ANN. In addition, the C-V characteristics are modeled by ANNs with a logarithmic scale for accuracy. The proposed model is implemented and simulated in SPICE simulator SIMetrix. The simulation results are compared with experimental results from a double-pulse tester to validate the proposed modeling methodology. The model is also compared with the Angelov model created by the Keysight MOSFET modeling software. The comparison results show that the proposed model is more accurate than the Angelov model. Besides, when compared to the Angelov model, the proposed model requires 30% less computation time when simulating a double pulse tester. In addition, the proposed modeling method also has better adaptability to model different types of SiC MOSFETs.Index Terms-SiC MOSFET, transient model, hybrid modeling, artificial neural network.

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Datasheet-Driven Compact Model of Silicon Carbide Power MOSFET Including Third-Quadrant Behavior

Cited by 24 publications

References 24 publications

Influence of driving and parasitic parameters on the switching behaviors of the SiC MOSFET

Influence of driving and parasitic parameters on the switching behaviors of the SiC MOSFET

Lookup Table-based Electro-Thermal Real-Time Simulation of Output Series Interleaved Boost Converter for Fuel Cell Applications

Hybrid Data-Driven Modeling Methodology for Fast and Accurate Transient Simulation of SiC MOSFETs

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