Pictogram Lifetime Model Winding Insulation

Research Project: Lifetime model winding insulation

Institute of Machine Components (IMA)

Development of a holistic lifetime model for the winding insulation of electrical machines on the basis of the acting damage mechanisms and their different load levels
[Photo: Philipp Mell]

The reliability of electric vehicles is a key aspect to satisfy the market requirements in terms of lifetime. However, a verified lifetime model of the critical electromechanical components is missing so far. Increases in transistor switching speed, voltage levels and frequency harmonics of the dynamically evolving inverters increase the electrical stress on the motor winding insulation and lead to partial discharges (PD), which can reduce the life of the electrical machine to an unacceptable level. The aging process of the winding insulation is associated with several influencing factors, including electrical, thermal and mechanical stresses. Therefore, this project investigates the effects of the main influencing factors on the insulation lifetime, resulting in a statistical lifetime model.

detailed project description (.pdf)

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IGF project 21658 N:  funding website.

Publications

  1. Mell, Philipp ; He, Chuxuan ; Dazer, Martin ; Beltle, Michael: Lifetime Model Winding Insulation. In: Proceedings of the FVV Transfer + Networking Event 2024 : FVV e.V., 2024
  2. Mell, Philipp ; Dazer, Martin ; Beltle, Michael: Reliability Assessment for Failure Mechanisms in Complex Electrified Systems. In: MTZ Worldwide. Bd. 85 (2024), Nr. 5, S. 76–79
  3. Mell, Philipp ; Dazer, Martin ; Beltle, Michael: Zuverlässigkeitsbewertung für Ausfallmechanismen an komplexen elektrifizierten Systemen. In: MTZ - Motortechnische Zeitschrift. Bd. 85 (2024), Nr. 5, S. 76–79
  4. Mell, Philipp ; Dazer, Martin ; He, Chuxuan ; Beltle, Michael: A novel ADT approach for partial discharge in electrical machines. In: 2023 Annual Reliability and Maintainablity Symposium, 2023 — IMA-ZUV 406 (peer-review)
  5. Mell, Philipp ; Karle, Fabian ; Herzig, Thomas ; Dazer, Martin ; Bertsche, Bernd: Accelerating Optimal Test Planning With Artificial Neural Networks. In: 2022 Annual Reliability and Maintainablity Symposium, 2022 — IMA-ZUV 371 (peer-review)
  6. Mell, Philipp ; Dazer, Martin ; Bertsche, Bernd: Wie lange läuft der E-Motor von morgen? In: WiGeP-News Juli 2022. (2022), Nr. 1, S. 9–10 — IMA-ZUV 395
  7. Mell, Philipp ; Arndt, Marco ; Dazer, Martin: Non-orthogonality in test design: practical relevance of the theoretical concept in terms of regression quality and test plan efficiency. In: 16th Probabilistic Safety Assessment & Management Conference (PSAM 16), 2022 — IMA-ZUV 390 (peer-review)

Contact

This image shows Philipp Mell

Philipp Mell

M. Sc.

Research Associate

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