By automating double-pulse testing of wide bandgap devices such as SiC and GaN power devices, you can cut setup and analysis time.
The need to reduce carbon emissions drives investments in electrical technologies, particularly in data centers and electric vehicles. In its most recent Elective Vehicle Outlook report, Bloomberg estimates a 27% increase in global electricity demand caused mostly by electrifying nearly all of road transport by 2050.
Wide bandgap (WBG) semiconductors, including gallium nitride (GaN) and silicon carbide (SiC), are replacing silicon-based power MOSFETs and IGBTs in switch-mode power supplies and motor drives. GaN and SiC devices have higher switching speeds, higher power density, higher frequency response, lower leakage, lower ON resistance, and higher operating temperatures than silicon. These characteristics result in greater operating efficiency. They can reduce energy use, making it easier to comply with regulatory and certification requirements as well as current JEDEC JC-70 wide bandgap power electronic conversion semiconductor standards. Compliance requires testing.
WBG brings new test methods to the table. As engineers continue to study WBG technologies, they learn more about the behaviors of these devices and their performance. The common transistor architecture for SiC and GaN is the MOSFET and HEMT, respectively. Both offer advantages over the other, but both come with their own set of measurement challenges.
While the tests required during design and production are like those of silicon-based devices, the adoption of WBG materials requires added rigor for higher voltage and current levels to accurately measure performance and long-term reliability. High-power devices such as SiC MOSFETs operate at voltages well over 1000 V, even as high as 5000 V. With current levels in the tens to hundreds of amps, it’s becoming more common for engineers to talk about kilowatt to megawatt power levels. These levels require new testing strategies and — more importantly — an emphasis on safety.
To fully validate SiC or GaN-based WBG devices, engineers must test several parameters using a test setup such as that shown in Figure 1. Parameters include:
- Switching loss: precise time alignment is critical. Nanosecond errors in capturing signals can result in incorrect results.
- Peak voltage: voltage spikes commonly occur during high-current, high-speed hard switching.
- Peak current: fast switching operation of WBG transistors causes sharp current spikes that stress devices and may reduce lifespan.
- Reverse-recovery charge: this behavior must be quantified to understand its contribution to total losses. Figure 2 shows reverse-recovery charge waveforms.
The preferred test method to measure the switching and diode reverse-recovery parameters of WBG devices is the double-pulse test (DPT). DPT can be an efficient process for making several critical measurements to help validate and optimize these power converter designs. Figure 3 shows a typical test circuit.
Performing DPT lets you:
- Guarantee specifications of power devices like MOSFETs and IGBTs.
- Confirm the actual value or deviation of the power devices or power modules.
- Measure switching parameters under various load conditions and validate performance across many devices.
To define a DPT signal, you need two pulses of different widths (Figure 4). The first, longer pulse establishes current in the inductor (shown in Figure 3) that replicates circuit conditions in a converter design. You’ll need to adjust the pulse width to get to the desired test current.
The second pulse is shorter than the first pulse to prevent the device from overheating but long enough to make the measurements.
You can use manual methods to create pulses with varying pulse widths, which can be time-consuming. Some of these methods include creating waveforms on a PC and uploading them to a function generator. Others use microcontrollers that can require more time to program.
As materials researchers and device engineers explore new and more advanced devices, such as those that could be based on Gallium Oxide, Aluminum Nitride, and even Diamond, new approaches to DPT methodology may arise.
Instead of the arbitrary function generator (AFG) outputting a programmed double pulse sequence, it can be programmed to output a series of equally-sized pulses. Cumulatively, these pulses can deliver the same current as the initial pulse in a normal DPT. Such an approach has been suggested in this peer-reviewed journal paper. The good news is that the instrumentation and the software that runs the test can be modified for new approaches.
Engineers interested in understanding the switching, timing, and reverse-recovery behaviors of WBG power devices can use automated DPT methods to shorten test time. Oscilloscopes with measurement software can automate test setup, execution, and analysis.
Figure 5 shows a typical setup screen. Adjust the first pulse width to get the desired switching current values. Then, adjust the second pulse to avoid destroying the power device. You can also set time gaps between the pulses.
Careful probing and optimization will help you get good results. You can take steps to make accurate and repeatable measurements. For example, removing voltage, current, and timing errors from the measurement. Automated measurement software eliminates manual steps, saving time and providing repeatable results.
DPT is the preferred test method to measure the switching parameters and evaluate the dynamic behaviors of power devices. Automated DPT setup and analysis can greatly reduce test times and achieve faster time to market for next-generation power converters. Tests can easily run with full remote control, letting you keep your distance from the high-voltage, high-current DUT for added safety.
Without the ability to measure critical values and ensure functionality, your ability to meet energy demands and achieve worldwide progress on carbon reduction can only go so far. By researching and testing new materials, we can get closer to the goal of meeting energy demands and adopting new efficiency standards. There’s still time to reduce Bloomberg’s estimated 27% increase.