Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/43327
Title: Encapsulation strategies for mechanical impact and damp heat reliability improvement of lightweight photovoltaic modules towards vehicle-integrated applications
Authors: LUO, Bin 
GOVAERTS, Jonathan 
Lisco, Fabiana
Eder, Gabriele
Breukers, Bram
RUTTENS, Bart 
D'HAEN, Jan 
VAN DYCK, Rik 
SIVARAMAKRISHNAN RADHAKRISHNAN, Hariharsudan 
Van Vuure, Aart Willem
POORTMANS, Jef 
Issue Date: 2024
Publisher: ELSEVIER
Source: Solar energy materials and solar cells, 273 (Art N° 112932)
Abstract: Lightweight modules are essential for next-generation vehicle-integrated photovoltaic (VIPV) applications, such as solar-powered cars, allowing integration of solar cells beyond the roof, and on the hood, boot and body panels, and thereby extending the driving range. However, the lightweight module 's reliability and corresponding degradation mechanisms under various environmental stresses are less researched. In this work, we investigate interconnection and encapsulation strategies to improve reliability against damp heat and mechanical impact. We fabricated lightweight mini modules, weighing around 3.45 kg/m 2 , and conducted hail impact and damp heat tests. These tests result in different failures, such as cracks in the solar cell, module delamination, and microcracks in the backsheet. By carrying out failure mechanism analysis and altering the fiber reinforcement in backsheet and encapsulation materials, we can increase resilience to these failure modes, thus providing guidance for the design of lightweight PV modules for next-generation VIPV.
Notes: Luo, B (corresponding author), Katholieke Univ Leuven, Oude Markt 13, B-3000 Leuven, Belgium.
bin.luo@imec.be
Keywords: VIPV;Lightweight PV;Interconnection and encapsulation strategies;Reliability
Document URI: http://hdl.handle.net/1942/43327
ISSN: 0927-0248
e-ISSN: 1879-3398
DOI: 10.1016/j.solmat.2024.112932
ISI #: 001244744500001
Rights: 2024 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
Category: A1
Type: Journal Contribution
Appears in Collections:Research publications

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