Long-Term Degradation Trend Prediction and Remaining Useful Life Estimation for Solid Oxide Fuel Cells
Abstract
:1. Introduction
- To improve the durability, a dynamic model of the ohmic ASR is proposed, which can accurately evaluate the performance degradation characteristics of the SOFC;
- Based on the established dynamic model, the PF algorithm is proposed to achieve the long-term prediction of the degradation trend and the accurate estimation of the RUL of the SOFC.
2. Nonlinear Dynamic Model of the SOFC
2.1. Energy Balance Sub-Model
2.2. Electrochemical Sub-Model
3. Degradation Trend Prediction and RUL Estimation of the SOFC
3.1. Particle Filter Algorithm
3.2. Prediction of the Degradation Trend Based on the PF Algorithm
3.3. Estimation of the RUL
Algorithm 1 RUL estimation algorithm |
End While End |
4. Results and Discussion
4.1. ASR Prediction Results of the Degradation Trend
4.2. RUL Prediction Results of the Degradation Trend
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Symbol | Definition | Value |
---|---|---|
number of cells | 5 | |
stack lumped thermal capacity | 5500 J·K−1 | |
active area | 100 cm2 | |
the initial mole fraction of hydrogen | 0.97 | |
the initial mole fraction of oxygen | 0.21 | |
the initial mole fraction of water vapor | 0.03 | |
minimal nominal acceptable voltage | 4 V | |
ideal gas constant | 8.3142 J·mol−1·K−1 | |
Faraday constant | 96,485 C·mol−1 | |
activation energy for the scale growth | 220 K J·mol−1 | |
activation energy for the oxide scale conductivity | 75.2 K J·mol−1 | |
rate constant for the thickness growth of the scale | 0.0126 cm2·s−1 | |
conductivity constant | 3.2 × 105 S·cm−1 |
PF | KF | |
---|---|---|
RMSE | 0.0008 | 0.0126 |
MAPE | 0.0430 | 1.4582 |
R2 | 0.9866 | 0.8895 |
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Cui, L.; Huo, H.; Xie, G.; Xu, J.; Kuang, X.; Dong, Z. Long-Term Degradation Trend Prediction and Remaining Useful Life Estimation for Solid Oxide Fuel Cells. Sustainability 2022, 14, 9069. https://doi.org/10.3390/su14159069
Cui L, Huo H, Xie G, Xu J, Kuang X, Dong Z. Long-Term Degradation Trend Prediction and Remaining Useful Life Estimation for Solid Oxide Fuel Cells. Sustainability. 2022; 14(15):9069. https://doi.org/10.3390/su14159069
Chicago/Turabian StyleCui, Lixiang, Haibo Huo, Genhui Xie, Jingxiang Xu, Xinghong Kuang, and Zhaopeng Dong. 2022. "Long-Term Degradation Trend Prediction and Remaining Useful Life Estimation for Solid Oxide Fuel Cells" Sustainability 14, no. 15: 9069. https://doi.org/10.3390/su14159069