干旱区生态环境知识资源中心

The first step in developing a life prediction model for photovoltaic (PV) modules is the identification of dominant failure modes/mechanisms for given environmental and operating conditions. Although important, the literature is very scarce. The Jet Propulsion Laboratory (JPL) approach consists of identifying the weakest link in module construction and the failure modes or mechanisms susceptible to the link are considered dominant. The failure mode and effects analysis/failure mode and effects criticality analysis approach, proposed and tried by a few authors, provides a more analytical alternative. It uses the risk priority number (RPN) as a ranking metric for failure modes prioritization. The RPN is a product of three parameters: severity of a failure (S), occurrence of the failure (O), and detection of the failure (D). Typically, the values for S, O, and D are assigned based on qualitative analyses. As such, the values assigned for the failure modes to those factors are highly subjective, leading to considerable variations from one analyst or design team to another. The main objective of this study is to move as far away as possible from this traditionally subjective approach to a formal, objective, and data-driven determination of RPN. The approach described in this paper relies on quantitative measures and sizable datasets. For the hot and dry climatic conditions of Phoenix, Arizona USA, solder bond failures and encapsulant discoloration are found to be the dominant failure modes.