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Linear viscoelastic characterization of electrically conductive adhesives used as interconnect in photovoltaic modules
Author(s) -
Springer Martin,
Bosco Nick
Publication year - 2020
Publication title -
progress in photovoltaics: research and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.286
H-Index - 131
eISSN - 1099-159X
pISSN - 1062-7995
DOI - 10.1002/pip.3257
Subject(s) - interconnection , viscoelasticity , materials science , photovoltaic system , electrical conductor , characterization (materials science) , adhesive , finite element method , material properties , computer science , mechanical engineering , composite material , structural engineering , nanotechnology , engineering , electrical engineering , computer network , layer (electronics)
Electrically conductive adhesives (ECAs) are incorporated into recent designs of photovoltaic (PV) modules and replace the traditional metallic solders as interconnects. This transition depicts a significant material change, and a proper understanding of the interconnects' mechanical response has not yet been established. However, such an understanding is necessary to (a) identify the driving forces for module degradation and failure, (b) allow for module design optimization, and (c) enable accurate lifetime predictions. This study summarizes the framework for the mechanical materials characterization and modeling of ECAs for PV applications. Only high‐fidelity material models are able to capture the rate and temperature dependency of the ECA interconnect and allow for accurate modeling of the materials response. A linear viscoelastic representation is found to describe the mechanical response of the ECAs sufficiently well. The effects of curing conditions and environmental exposure are investigated, and material models for a variety of ECAs are reported and prepared for the use in numerical simulations. A finite element simulation of a generic submodel of a shingled cell module is used to highlight the need for high‐fidelity material models and demonstrates the error made in the predicted stress states by using less sophisticated models.