pictogramm Reliability process for photovoltaic & battery inverters

Research Project: Reliability process for photovoltaic & battery inverters

Institute of Machine Components (IMA)

Development and evaluation of an efficient and reliable methodology for reliability prediction and lifetime prediction of photovoltaic & battery inverters and their critical components.
[Photo: Achim Benz]

In the international market, service life and reliability are significant quality criteria for holding one's own against the competition. Especially in the cost-driven market segment of renewable energies, reliability is the key for load-oriented dimensioning with which the service life targets can be achieved in a resource-efficient way. Current approaches for the reliability assessment of electronic components are based on hypotheses that do not allow for a valid reliability analysis. In this project, therefore, a consistent methodology for the reliability analysis and validation of inverters is to be developed. The project mainly consists of the work packages: Component and device analysis, failure and aging mechanisms, development of a new method, field data analysis and the evaluation of test procedures.

detailed project description (.pdf)

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Funded by BMWI
Funding code: 03EE1054B

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Publications

  1. Hintz, Kim ; Dazer, Martin: Evaluation of the Influence of Reliability and Repair Strategy on the Performance of a PV System (2023)
  2. Benz, Achim ; Grundler, Alexander ; Herzig, Thomas ; Dazer, Martin ; Bertsche, Bernd: Reliability Demonstration Test Planning for Field Load Spectra – an Approach for Identifying the Optimal Test Parameters considering Individual Cost and Time Constraints. In: Annual Reliability and Maintainability Symposium 2022 Proceedings, 2022. — ISBN 978-1-6654-2432-5 — IMA-DT 382 (peer-review)
  3. Benz, Achim ; Grundler, Alexander ; Dazer, Martin ; Bertsche, Bernd: Influence of Operating Load Spectra Shapes on Reliability Demonstration Test Planning. In: 16th Probabilistic Safety Assessment & Management Conference (PSAM 16), 2022 — IMA-DT 394 (peer-review)
  4. Benz, Achim ; Grundler, Alexander ; Dazer, Martin ; Bertsche, Bernd: Deriving Prior Knowledge from Lifetime Simulations for Reliability Demonstration while Considering the Uncertainty of the Lifetime Model. In: Proceedings of the 31st European Safety and Reliability Conference : Research Publishing, Singapore, 2021. — ISBN 978-981-18-2016-8 — IMA-DT 375 (peer-review)

Contact

This image shows Achim Benz

Achim Benz

M. Sc.

Academic Staff

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