David Bigaud

Accelerated degradation testing of a photovoltaic module

Abstract. There are a great many photovoltaic (PV) modules installed around the world. Despite this, not enough is known about the reliability of these modules. Their electrical power output decreases with time mainly as a result of the effects of corrosion, encapsulation discoloration, and solder bond failure. The failure of a PV module is defined as the point where the electrical power degradation reaches a given threshold value. Accelerated life tests (ALTs) are commonly used to assess the reliability of a PV module. However, ALTs provide limited data on the failure of a module and these tests are expensive to carry out. One possible solution is to conduct accelerated degradation tests. The Wiener process in conjunction with the accelerated failure time model makes it possible to carry out numerous simulations and thus to determine the failure time distribution based on the aforementioned threshold value. By this means, the failure time distribution and the lifetime (mean and uncertainty) can be evaluated.

Behavior analysis of machines and system air hemispherical spindles using finite element modeling

Purpose – The spindle behavior of machines and systems depends largely on the choice and design quality of the mechanical components used for the displacement between different parts. As far as very high technology is concerned, air bearings are suitable, for instance, for machining a telescope mirror or for systems used in medical applications that require a micro and nanometric resolution in displacement. Therefore, air bearings play a crucial role in ensuring spindle stability in machines and systems. The static and dynamic behavior of air spindles is dependent on several parameters, such as external load, dimensions, supply pressure, manufacturing capability and fluid properties.Design/methodology/approach – This paper presents a methodology for the calculation and analysis of the stability and reliability of machine and system spindles supported by air hemispherical bearings. The static and dynamic characteristics of air spindles are calculated using the finite element method (FEM). The stochastic Re...

Photovoltaic system lifetime prediction using Petri networks method

Photovoltaic modules and systems lifetime and availability are difficult to determine and not really well-known. This information is an important data to insure the installation performance of such a system and to prepare its recycling. The aim of this article is to present a methodology for the availability and lifetime evaluation of a photovoltaic system using the Petri networks method. Each component - module, wires and inverter - is detailed in Petri networks and several laws are used in order to estimate the reliability. Several guides (FIDES, MIL-HDBK-217 ...) allow determining the reliability of electronic components using collections of data. For photovoltaic modules, accelerated life testing are carried out for the evaluation of the lifetime which is described by a Weibull distribution. Results obtained show that Petri networks are very useful to simulate lifetime thanks to its intrinsic modularity.

Reliability evaluation of a photovoltaic module using accelerated degradation model

Many photovoltaic modules are installed all around the world. However, the reliability of this product is not enough really known. The electrical power decreases in time due mainly to corrosion, encapsulation discoloration and solder bond failure. The failure of a photovoltaic module is obtained when the electrical power degradation reaches a threshold value. Accelerated life tests are commonly used to estimate the reliability of the photovoltaic module. However, using accelerated life tests, few data on the failure of this product are obtained and the realization of this kind of tests is expensive. As a solution, an accelerated degradation test can be carried out using only one stress if parameters of the acceleration model are known. The Wiener process associated with the accelerated failure time model permits to carry out many simulations and to determine the failure time distribution when the threshold value is reached. So, the failure time distribution and the lifetime (mean and uncertainty) can be evaluated.

Reliability Estimation of Mechanical Components Using Accelerated Life Testing Models

This chapter presents an overview of using accelerated life testing (ALT) models for reliability estimation on mechanical components. The reliability is estimated by considering two test plans: a classical one testing a sample system under accelerated conditions only and a second plan with previous accelerated damage. The principle of the test plan with previous accelerated damage is testing the sample under step-stress. In the beginning (until time N 1), the sample is tested under stress s 1 (accelerated testing: \(s_{1}>s_{0}\)); when the tested units have used many of their “resources,” the stress s 1 is replaced by the operating conditions s 0 (until the time N 2). Therefore, failure times under the accelerated conditions can be used to estimate reliability function in operating conditions. The time transformation function is considered as log-linear and four types of estimation are studied: parametric, Extended Hazard Regression (GPH), semi-parametric, and nonparametric models. The chapter is illustrated by a simulation example of ball bearings testing. The results are used to analyze and compare these estimation methods. The simulations have been performed both with censored data and without censoring, in order to examine the asymptotic behavior of the different estimates.