Projektdetaljer
Beskrivelse
Abstract:
The concept of Clean Aviation (CA) will promote ever-evolved sustainability and green-tech innovation in terms of the vision of addressing the ambition target of the European Green Deal, which set a goal of the reduction of carbon-dioxide emission and consequently satisfy the production demand of novel aircraft in the future. Taking into account the elevated requirement of aircraft system associated with MW propulsive power and the diverse load profile at several distinguish level voltage, the power distribution network of CA must integrate a significant amount of lightweight power converters and devices, whose degradation or failure were found one of the major factors that lead to the catastrophic consequence of CA. In this context, the reliability framework will be an urgent challenge of the CA development that will be able to assess the condition of the components and overall system ahead of their failure, based on continuous high-frequency monitoring. By applying state-of-the-art techniques such as the Internet of Things (IoT), artificial intelligence (AI) and smart sensor deployment, the performance of monitoring, operation and prediction of aviation systems tend to be improved by feeding tremendous measurement, simulation and historical data, which currently are involved into the establishment of digital twin (DT) application. DT has received increased attention as effective support for the prognosis and health monitoring (PHM) for industries that instead of the conventional aging experiment, on the other hand, avoid the high cost of periodic, unscheduled maintenance and unexpected outage.
In this project, data-driven techniques are utilized to improve the reliability framework of the power distribution network based on the development of DT and PHM for the electronics, where the majority of work will focus on parameter identification and the prediction of potential degradation and failure. Regarding the high cost of aging experiments for the degradation observation of electronics, firstly the development of DT will be explored by carrying out simulation experiments in the microgrid lab. Eventually, the effectiveness of the data-driven system identification will be evaluated to prove the fidelity of the virtual representation of the devices. At the next stage, the monitoring of the system parameters such as voltage, harmonic and temperature, etc., will be analyzed and then integrated to report a novel PHM approach that aims to address the awareness of the deterioration ahead of the few remaining lifetimes of the electronic devices.
Funding: Self-funded
The concept of Clean Aviation (CA) will promote ever-evolved sustainability and green-tech innovation in terms of the vision of addressing the ambition target of the European Green Deal, which set a goal of the reduction of carbon-dioxide emission and consequently satisfy the production demand of novel aircraft in the future. Taking into account the elevated requirement of aircraft system associated with MW propulsive power and the diverse load profile at several distinguish level voltage, the power distribution network of CA must integrate a significant amount of lightweight power converters and devices, whose degradation or failure were found one of the major factors that lead to the catastrophic consequence of CA. In this context, the reliability framework will be an urgent challenge of the CA development that will be able to assess the condition of the components and overall system ahead of their failure, based on continuous high-frequency monitoring. By applying state-of-the-art techniques such as the Internet of Things (IoT), artificial intelligence (AI) and smart sensor deployment, the performance of monitoring, operation and prediction of aviation systems tend to be improved by feeding tremendous measurement, simulation and historical data, which currently are involved into the establishment of digital twin (DT) application. DT has received increased attention as effective support for the prognosis and health monitoring (PHM) for industries that instead of the conventional aging experiment, on the other hand, avoid the high cost of periodic, unscheduled maintenance and unexpected outage.
In this project, data-driven techniques are utilized to improve the reliability framework of the power distribution network based on the development of DT and PHM for the electronics, where the majority of work will focus on parameter identification and the prediction of potential degradation and failure. Regarding the high cost of aging experiments for the degradation observation of electronics, firstly the development of DT will be explored by carrying out simulation experiments in the microgrid lab. Eventually, the effectiveness of the data-driven system identification will be evaluated to prove the fidelity of the virtual representation of the devices. At the next stage, the monitoring of the system parameters such as voltage, harmonic and temperature, etc., will be analyzed and then integrated to report a novel PHM approach that aims to address the awareness of the deterioration ahead of the few remaining lifetimes of the electronic devices.
Funding: Self-funded
| Status | Igangværende |
|---|---|
| Effektiv start/slut dato | 01/10/2023 → 30/09/2026 |
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