Prediction of the remaining useful life using simple Gaussian process particle filter
碩士 === 國立交通大學 === 統計學研究所 === 105 === In response to the worldwide energy crisis and environmental issues, proton exchange membrane fuel cell is regarded as a very important alternative energy sources. However, the current fuel cell applications are also limited by the lack of life issues. Therefore,...
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| Format: | Others |
| Language: | en_US |
| Published: |
2016
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| Online Access: | http://ndltd.ncl.edu.tw/handle/2q37m3 |
| Summary: | 碩士 === 國立交通大學 === 統計學研究所 === 105 === In response to the worldwide energy crisis and environmental issues, proton exchange membrane fuel cell is regarded as a very important alternative energy sources. However, the current fuel cell applications are also limited by the lack of life issues. Therefore, the remaining useful life of the battery management is significant. The particle filter is considered to be successful in the prediction of the remaining life of the fuel cell. In this study, we propose a Simple Gaussian Process Particle Filter to predict the remaining life of the battery, and it is more flexible than traditional particle filter. We use this method to achieve a more accurate life prediction.
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