Ageing in aircraft electromechanical chain: design of thermal cycling bench for winding elements

Dreuilhe, Sarah; Pin, S.; Fetouhi, Louiza; Stemmer, Susanne; Belijar, Guillaume; Albert, Larry

doi:10.1109/eic49891.2021.9612334

Cited by 4 publications

(4 citation statements)

References 11 publications

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“…Similarly, air-cooled motorettes are thermally aged in [117], and the corresponding test bench is shown in Figure 17. Challenges of thermal ALTs at variable temperatures are represented by the controller tuning [118] and the delay in the temperature feedback. These aspects result in changes in the applied temperature profiles making difficult the results comparison.…”

Section: Methodsmentioning

confidence: 99%

“…However, due to the temperature fluctuations, ensuring accurate temperature measurements is challenging and the thermal sensor location becomes crucial. Sometimes thermal model or FEA of the sample under test is developed to precisely identify the exact winding hot-spot location and consequently install the thermal sensors [108,118]. An example of a motorette and associated lumped parameter thermal network is depicted in Figure 18.…”

Section: Specimens' Choicementioning

confidence: 99%

“…An example of a motorette and associated lumped parameter thermal network is depicted in Figure 18. In some other cases, multiple thermal sensors embedded inside the motorette are also used, and by post-processing the recorded temperature profiles, the effect of the temperature fluctuations is mitigated, as in [117][118][119].…”

Section: Specimens' Choicementioning

confidence: 99%

“…Since the PD signal can reach a frequency of up to 1.5 GHz, while the switching noise is mainly located between 0 and 400 MHz, a 500 MHz high-pass filter is often used to eliminate the switching noise. In some other cases, multiple thermal sensors embedded inside the motorette are also used, and by post-processing the recorded temperature profiles, the effect of the temperature fluctuations is mitigated, as in [117][118][119].…”

Section: Experimental Platform Setup For Electrical Agingmentioning

confidence: 99%

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Insulation for Rotating Low-Voltage Electrical Machines: Degradation, Lifetime Modeling, and Accelerated Aging Tests

Zhou,

Giangrande,

et al. 2024

Energies

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The low-voltage electric machine (EM) is a core technology for transportation electrification, and features like high power density and compact volume are essential prerequisites. However, these requirements are usually in conflict with the reliability property of EM, especially in the safety-critical industry such as aviation. Therefore, an appropriate balance between high-performance and reliability needs to be found. Often, the over-engineering method is applied to ensure safety, although it might have a detrimental effect on the EM volume. To address this issue, the EM reliability assessment is included at the EM design stage through the physics of failure (PoF) theory. In EMs, the windings play a key role in electromechanical energy conversion, but their insulation system is subject to frequent failure and represents a reliability bottleneck. Therefore, in-depth research on the root causes of insulation breakdown is beneficial for EM reliability improvement purposes. Indeed, increasing awareness and knowledge on the mechanism of the insulation degradation process and the related lifetime modeling enables the growth of appropriate tools for achieving reliability targets since the first EM design steps. In this work, the main aspects of the insulation system, in terms of materials and manufacturing, are first reviewed. Then, the principal stresses experienced by the winding insulation system are deeply discussed with the purpose of building a profound understanding of the PoF. Finally, an overview of the most common insulation lifetime prediction models is presented, and their use for accomplishing the reliability-oriented design (RoD) and the remaining useful life (RUL) estimation are examined.

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Section: Methodsmentioning

confidence: 99%

Section: Specimens' Choicementioning

confidence: 99%