Date of Award

6-30-2016

Document Type

Open Access Dissertation

Department

Electrical Engineering

First Advisor

Enrico Santi

Abstract

In recent times, the development of high power density and high efficiency power converters has become critical in power electronics applications like electric vehicles, aircrafts, electric ships and so on. High-switching-frequency and high-temperature operation are required to achieve this target. However, these requirements are exceeding the theoretical material-related limits of silicon (Si) based devices. The emerging wide bandgap power semiconductor technology is a promising solution to meet these requirements. Silicon Carbide (SiC) and Gallium Nitride (GaN) are the most promising among all wide bandgap semiconductor materials. SiC and GaN have almost a three times larger bandgap (about 3eV), compared with Si (about 1eV). The breakdown electric field of SiC and GaN is one order of magnitude higher than that of Si. The higher breakdown electric field enables the design of wide bandgap power devices with a thinner and higher doped voltage blocking layer. For unipolar power devices, this can yield a lower on-state voltage drop and conduction loss. For bipolar power devices, this can lead to a shorter switching time and lower switching loss. The high thermal conductivity of SiC, together with large bandgap, allows SiC-based devices to operate at temperatures exceeding 200oC. All of these properties make wide bandgap semiconductor devices a promising alternative to Si-based devices.

The research work in this Ph.D dissertation can be broadly divided into two parts: the development of power device models, and the development of loss models for wide bandgap power devices.

First, in order to characterize the switching performance of GaN High Electron Mobility Transistor (HEMT), a simple and accurate circuit-simulator compact model for a normally-off GaN HEMT device is developed. The model parameters can be easily extracted from static I-V characteristics and C-V characteristics. This model captures reverse channel conduction, which is a very important feature for circuit designers. A parameter extraction method is proposed. A double pulse test-bench is built to test the switching behavior of GaN HEMT. The accuracy of the proposed GaN HEMT model is validated under resistive and inductive switching conditions, and simulation results match well with experiments in terms of device switching waveforms.

Second, the static and switching characterizations of a SiC MOSFET’s body diode are carried out. The static characterization of SiC MOSFET’s body diode is done using a curve tracer and a double pulse test bench is built to characterize the inductive switching behavior of SiC MOSFET’s body diode. The reverse recovery of SiC MOSFET’s body diode is shown at different junction temperatures, forward conduction currents and current commutation slopes. In order to evaluate the performance of SiC MOSFET’s body diode in different applications, an accurate physics-based diode model is introduced to perform simulations of SiC MOSFET’s body diode. The validation of the body diode model is presented to prove the accuracy of the device model over a wide temperature range.

Third, an accurate analytical loss model that takes into account parasitic elements for power converters utilizing SiC MOSFETs and SiC Schottky diodes is proposed. A novel feature of this loss model is that it considers the PCB parasitic elements in the circuits and the ringing loss. The switching process is analyzed in details, and the typical switching waveforms are given. The analytical results are compared with experimental results to verify the proposed analytical loss model.

Finally, a performance projection method and scalable loss model for SiC MOSFETs and SiC Schottky diodes are developed. To our knowledge, this is the first scalable loss model that provides performance projection capability for future SiC MOSFETs and SiC Schottky diodes. The parameters of these models are extracted from device datasheets by using a curve fitting method. Loss estimation of future SiC MOSFETs and SiC Schottky diodes can be performed based on the proposed scalable loss model.

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