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Long-term capacitance variation characteristics, law extraction, single and collaborative prediction of film capacitors at room temperature and humidity.
- Source :
-
Microelectronics Reliability . Dec2022, Vol. 139, pN.PAG-N.PAG. 1p. - Publication Year :
- 2022
-
Abstract
- With the renewable energy application fields of film capacitors gradually expanding, mining film capacitors' data is an important issue. When the aging mechanism and environment are unfamiliar, it will be hard to extract the capacitance's variation law and predict its changes. At the same time, the parallel operation of film capacitor components also brings practical needs and data basis for collaborative prediction. In this work, the capacitance of five film capacitors at room temperature and humidity for 70 days was measured and the characteristics of capacitance variation were analyzed. Then, the capacitance law extraction, single prediction, and collaborative prediction methods for film capacitors were proposed based on the smoothing splines theory. Finally, the effectiveness and application potential of the single prediction and collaborative prediction methods were verified by actual data. The performance of the single prediction and collaborative prediction methods is evaluated by error analysis. The single prediction and collaborative prediction methods proposed in this work can also provide a reference for the prediction and evaluation of other parameters like equivalent series resistance of film capacitors, and help to effectively and accurately explore the aging mechanism. • We measured the capacitance for 70 days at room temperature and humidity and analyzed the characteristics. • Based on smooth splines theory, the law extraction, single prediction, and collaborative prediction methods were constructed. • This work will provide a reference for predicting and evaluating other parameter such as the equivalent series resistance of film capacitors, helping to monitor the state and explore the aging mechanism effectively and accurately. [ABSTRACT FROM AUTHOR]
- Subjects :
- *SPLINE theory
*ELECTRIC capacity
*HUMIDITY
*FORECASTING
*RENEWABLE energy sources
Subjects
Details
- Language :
- English
- ISSN :
- 00262714
- Volume :
- 139
- Database :
- Academic Search Index
- Journal :
- Microelectronics Reliability
- Publication Type :
- Academic Journal
- Accession number :
- 160335792
- Full Text :
- https://doi.org/10.1016/j.microrel.2022.114845