Model Associated with the Study of the Degradation Based on the Accelerated Test: A Literature Review

Abstract

Most manufacturers of solar modules guarantee the minimum performance of their modules for 20 to 25 years, and 30-year warranties have been introduced. The warranty typically guarantees that the modules will perform to at least 90% capacity in the first 10 years and to at least 80% in the following 10 -15 years. Early degradation resulting from design flaws, materials or processing issues is often apparent from startup to the first few years in service. Importantly, many module failures and performance losses are the result of gradual accumulated damage resulting from long-term outdoor exposure in harsh environments, referred. Many of these processes occur on relatively long time scales and the various degradation processes may be chemical, electrical, thermal or mechanical in nature. These are either initiated or accelerated by the combined stresses of the service environment, in particular solar radiation, temperature and moisture, and other stresses such as salt air, wind and snow. Accelerated Life Testing (ALT) test methodology is normally predicated on first being able to reproduce a specific degradation or failure mode without altering it (correlation); and, second, to produce that result in less than real-time acceleration. Degradation and failure may result when an applied stress exceeds material or product strength. This may be a one-time catastrophic event, the result of cyclic fatigue, or a gradual decline in requisite properties due to ageing mechanisms. Engineers in the manufacturing industries have used accelerated test (AT) experiments for many decades. The purpose of AT experiments is to acquire reliability information quickly. Test units of a material, component, subsystem or entire systems are subjected to higher-than-usual levels of one or more accelerating variables such as temperature or stress. Then the AT results are used to predict life of the units at use conditions. The extrapolation is typically justified (correctly or incorrectly) on the basis of physically motivated models or a combination of empirical model fitting with a sufficient amount of previous experience in testing similar units. The need to extrapolate in both time and the accelerating variables F. Dia et al. 50 generally necessitates the use of fully parametric models. Statisticians have made important contributions in the development of appropriate stochastic models for AT data [typically a distribution for the response and regression relationships between the parameters of this distribution and the accelerating variable(s)], statistical methods for AT planning (choice of accelerating variable levels and allocation of available test units to those levels) and methods of estimation of suitable reliability metrics. This paper provides a review of many of the AT models that have been used successfully in this area.

Degradation of Materials and Products Described with Eyring’s Rate Process Theory

“…16 Theoretically, eq 31 and its generalized form after replacing [w] with [S] is consistent with other theoretically derived equations in literature, 2,5,17,18 and thus, it can be used to model the degradations of a completely different system like photovoltaic module. 5,19 Based on JPL's recommendation, 20 Pan et al 21 proposed the following empirical model to describe the power output of photovoltaic modules:…”

“…Equation 32 is identical to the empirical equations found in the dielectric breakdown process while [S] is replaced with the external electric field strength [E] 14,15 and in the lifetime determinations of solids in terms of mechanical strength for 50 different types of materials while [S] is replaced with the external mechanical tensile strength [σ]. 16 Theoretically, eq 31 and its generalized form after replacing [w] with [S] is consistent with other theoretically derived equations in literature, 2,5,17,18 and thus, it can be used to model the degradations of a completely different system like photovoltaic module. 5,19 Based on JPL's recommendation, 20 Pan et al 21 proposed the following empirical model to describe the power output of photovoltaic modules:…”

“…Theoretically, eq and its generalized form after replacing [ w ] with [ S ] is consistent with other theoretically derived equations in literature, ,,, and thus, it can be used to model the degradations of a completely different system like photovoltaic module. , Based on JPL’s recommendation, Pan et al proposed the following empirical model to describe the power output of photovoltaic modules: D ( t ) = 1 − exp ( − b t a ) with the parameter “a” approximately equal to “3” and “b” dependent on test conditions. This equation was confirmed by other authors…”

“…Using accelerated stability tests of a product under accelerated stress within a short time frame like a few months to estimate the shelf life at ambient conditions will be very imminent and economical. Theoretical models or empirical regressed mathematical equations have been extensively explored to achieve this goal. − Accelerated stability test conditions in pharmaceutical and nutraceutical areas are typically high temperature and high humidity levels above ambient conditions. For example, the ICH (the International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use) guideline stipulates that the accelerated condition is 40 °C/75% RH (relative humidity), and the ambient condition is 25 °C/60% RH.…”

Accelerated aging test modeling applied to solar mirrors

“…Basic considerations on Arrhenius relationship Temperature is a common stress that accelerates the degradation of a material because it accelerates kinetic processes. Most experimental data obtained with the temperature stress factor are modeled with the Arrhenius relationship, [13][14][15] which assumes that a chemical degradation process is controlled by a reaction rate constant k, as given by Eq. 2, where γ is the frequency factor, E a is the apparent activation energy (kJ/mol), R is the ideal gas constant (kJ/mol/K) and T is the temperature (K):…”