Presentation
18 September 2018 Development of methodology for service life prediction of PV backsheets (Conference Presentation)
Xiaohong Gu, Chen-An Wang, Yadong Lyu, Jae Hyun Kim, Andrew Fairbrother, Lakesha Perry, Deborah Jacob, Tinh Nguyen, Stephanie Watson
Author Affiliations +
Abstract
Accelerated laboratory testing has been recognized as a common means to simulate in-field exposure in a time-saving way, however, caution is needed as highly accelerated stresses can cause degradation which is never observed in the field. In this work, the effects of the environmental factors on backsheet degradation have been investigated using a commercial PPE backsheet (polyethylene terephthalate (PET/PET/ethylene-vinyl acetate (EVA)). The PPE films were exposed to NIST SPHERE (Simulated Photodegradation via High Energy Radiant Exposure) under different UV intensities, wavelengths, temperatures and humidities. The chemical and optical degradation of the backsheets were examined by FTIR and UV-vis spectroscopy. The reciprocity law and action spectrum were studied and the activation energy for PPE degradation was calculated. A preliminary statistical model for predicting the service life of the PPE backsheet has been established based on the SPHERE exposure data and further validated by the initial degradation of the fielded PPE in Florida, Arizona and Maryland.
Conference Presentation
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xiaohong Gu, Chen-An Wang, Yadong Lyu, Jae Hyun Kim, Andrew Fairbrother, Lakesha Perry, Deborah Jacob, Tinh Nguyen, and Stephanie Watson "Development of methodology for service life prediction of PV backsheets (Conference Presentation)", Proc. SPIE 10759, New Concepts in Solar and Thermal Radiation Conversion and Reliability, 107590D (18 September 2018); https://doi.org/10.1117/12.2323423
Advertisement
Advertisement
KEYWORDS
Personal protective equipment

Photovoltaics

Optical spheres

Data modeling

FT-IR spectroscopy

Humidity

Statistical analysis

Back to Top