Grants and Contracts Details
Description
Abstract
Electric propulsion is an emerging technology that can significantly improve the energy
efficiency, mitigate carbide emission and acoustic noise, as well as reduce operation cost
for transportation tools, such as electric aircraft, electric vehicles, and electric shipboards.
However, for these safety-critical applications, reliability of the propulsion drive systems
has received very limited attention, although electric propulsion has grown rapidly over
the past years.
This project aims to develop digital twin technologies for electric propulsion drive
systems used in transportation applications. Specifically, targeting at the semiconductor
switching faults in power inverters of propulsion drives, an online non-invasive lifetime
prediction model and diagnostic model will be developed in this proposed research. The
circuit topology of the power inverter under investigation here is a three-level active
neutral point clamped (ANPC) inverter due to its multiple performance benefits for electric
propulsion applications, such as high-quality output waveforms, low dv/dt in the output
voltage, and high dc-bus voltage withstanding capability.
The online prediction digital model is to estimate the instantaneous junction
temperature and the remaining power cycling lifetime of the power inverter, based on
high-fidelity lifetime degradation model, junction-to-case thermal model of the inverter,
and the sensed baseplate or case temperature of the semiconductor switches. The
proposed lifetime prediction model will be validated in the power cycling acceleration tests
on semiconductor switches in the laboratory, before it will be embedded into the
microprocessors of the propulsion drives.
The online diagnostic digital model is to detect and identify the switching faults in the
power inverters of the propulsion drive systems. The input information of the diagnostic
model includes the measured dc-bus voltage and output AC current, as well as the
instantaneous information of the switching states of the inverter, which is typically all
available in the microcontrollers of propulsion drives. A faulty switch will be detected and
identified based on comparing the expected neutral point current to the measured real-
time values.
The proposed online lifetime prediction model and diagnostic model will be
experimentally verified in an existing 50-kW three-phase three-level ANPC inverter in the
laboratory. Once the function of the prognostic and diagnostic models is confirmed, these
digital models will be embedded into the system microprocessor. As a result, an effective
digital twin for monitoring the health condition of the semiconductor devices in power
inverters will be established, which improves the reliability of propulsion drives and avoid
accidents in transportation applications.
Status | Finished |
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Effective start/end date | 9/1/21 → 11/30/23 |
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