Advanced Imaging and Machine Learning for PV Quality Assurance
At a glance
- Project leader : Dr. Evelyne Knapp
- Co-project leader : Dr. Sandra Jenatsch
- Deputy of project leader : Mattia Battaglia
- Project team : Jens Baier, Salome Berger, Ennio Comi, David Kempf, Dr. Christoph Kirsch, Hartmut Nussbaumer
- Project status : ongoing
- Funding partner : Innosuisse (Innovationsprojekt / Projekt Nr. 58054.1 IP-EE)
- Project partner : Fluxim AG, Solaronix S.A.
- Contact person : Evelyne Knapp
Description
A multi-imaging setup is developed for investigating lab-scale solar cells and for obtaining spatially resolved information about the cell quality. Machine learning is used to estimate parameters for a physical FEM model that serves as a digital twin for further optimization.
Publications
-
Comi, Ennio; Knapp, Evelyne; Battaglia, Mattia; Kirsch, Christoph; Weidmann, Stefano; Jenatsch, Sandra; Hiestand, Roman; Bonmarin, Mathias; Ruhstaller, Beat; et al.,
2022.
Electro-thermal model for lock-in infrared imaging of defects in perovskite solar cells [paper].
In:
EU PVSEC Proceedings.
8th World Conference on Photovoltaic Energy Conversion, Milan, Italy, 26-30 September 2022.
WIP.
pp. 241-246.
Available from: https://doi.org/10.4229/WCPEC-82022-2BO.8.3