Abstract
Acceleration Factor prediction for accelerated life testing of photovoltaic (PV) modules plays a major role in estimating the reliability of modules in field. Accelerated stress tests are designed in such a way that the test replicates the failure mechanism that the module experiences outdoor. However, in most cases of PV modules, complete data on degradation measurement (from qualification testing and field exposure) is not available explicitly and sometimes the accelerated testing standard for some failure modes may not even be established. In such cases, it is hard to design the test plan and determine the degradation threshold or number of hours (or cycles) required to run the accelerated tests for estimating activation energy. This paper presents a novel approach in determining the acceleration factor based on partially available data from field measurements and uses it for damp heat testing of PV modules. Utilizing the available meteorological and degradation data, each field is considered as test environment with varying stress levels and a simple linear model is used for predicting the degradation threshold of DH1000 for field equivalent 25 years. Finally, the results are validated from the known qualification data and the acceleration factor plot for different regions is presented.
Original language | English (US) |
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Title of host publication | 2018 Annual Reliability and Maintainability Symposium, RAMS 2018 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Volume | 2018-January |
ISBN (Print) | 9781538628706 |
DOIs | |
State | Published - Sep 11 2018 |
Event | 2018 Annual Reliability and Maintainability Symposium, RAMS 2018 - Reno, United States Duration: Jan 22 2018 → Jan 25 2018 |
Other
Other | 2018 Annual Reliability and Maintainability Symposium, RAMS 2018 |
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Country/Territory | United States |
City | Reno |
Period | 1/22/18 → 1/25/18 |
Keywords
- Accelerated Life Testing (ALT)
- Acceleration Factor (AF)
- Photovoltaic (PV) Modules
ASJC Scopus subject areas
- Safety, Risk, Reliability and Quality
- General Mathematics
- Computer Science Applications