A Component Level Digital Twin Model for Power Converter Health Monitoring

Abstract

The proliferation of Power Electronic Converters (PECs) has had a pervasive affect in a variety of industries including the power generation, automotive and aerospace sectors, where their use brings reliability to the forefront, especially in applications where safety critical and harsh environments are experienced. Continuous improvements in the power density and efficiency through extensive research into new semiconductor technologies, passive components, circuit topologies and control methodologies has seen the performance of PECs improve indubitably. However, the manifestation of stresses occurring from significant heating due to high currents and switching frequencies; which over time can cause degradation in the performance of PEC components is still a real concern. This paper outlines a methodology for monitoring the degradation of PECs over the operational lifetime by utilizing a component level, physics based Digital Twin (DT). As well as providing a methodology for the real time comparison of parameters to realize the onset of faults subjected to operational stresses, the DT also provides a novel method of training a classifier by simulating the faults within the PEC, a process that in reality, would be difficult to achieve from a physical device. Feature extraction is via Wavelet Scattering and classification is provided using a Support Vector Machine (SVM) approach. The overall approach is one that is novel and expandable to a wide range of PEC topologies and will be beneficial to the optimization and maintenance of PECs in a variety of platforms.INDEX TERMS Digital twin, power electronics, reliability, power system simulation, real-time systems, health monitoring, PHM, wavelet scattering, support vector machine.

Review of Electric Vehicle Testing Procedures for Digital Twin Development: A Comprehensive Analysis

“…In [61], a data-driven DT model is proposed for preventing incipient inter-turn short-circuit faults in permanent magnet synchronous motors. In [62], the authors outline a methodology for monitoring and diagnosing the degradation of power electronic converters based on DTs. In [63], an approach for the early-stage degradation of fuel cells and its prediction is addressed using DT, which is tolerant to different degradation patterns and can achieve real-time degradation prediction.…”

Query-and-Response Digital Twin Framework using a Multi-domain, Multi-function Image Folio

“…A DT, designed for distributed photovoltaic (PV) systems, excels in identifying electrical faults but does not extend beyond the electrical domain [13]. Further, a method for monitoring and assessing the health of power electronic converters using DTs is demonstrated, focusing primarily on predicting component degradation [14]. A study detailed the use of DTs for threephase power converters with a particular focus on monitoring the degradation of the output LC filter [15].…”

Forecasting Framework for Digital Twins

“…However, they primarily address component-level applications and fall short of extending their findings to system-wide forecasting or proactive power management. Wileman et al 14 developed a component-level digital twin to monitor the health of power converters using physics-based models. This demonstrates the precision that digital twins can achieve at the component-level.…”