Online identification of a link function degradation model for solid oxide fuel cells under varying-load operation. (12th January 2022)
- Record Type:
- Journal Article
- Title:
- Online identification of a link function degradation model for solid oxide fuel cells under varying-load operation. (12th January 2022)
- Main Title:
- Online identification of a link function degradation model for solid oxide fuel cells under varying-load operation
- Authors:
- Chi, Yingtian
Qiu, Yiwei
Lin, Jin
Song, Yonghua
Hu, Qiang
Li, Wenying
Mu, Shujun - Abstract:
- Abstract: Prognostic is a potential tool for improving the durability of solid oxide fuel cells (SOFCs), which usually involves building a degradation model for prediction. However, the existing degradation models based on parallel constant operation datasets are inaccurate for integration with operation optimization and control problems of SOFCs under varying-load operation due to the nonuniform degradation behaviors. To address this issue, a link function degradation model is proposed, and its parameters are identified online with a cyclic batch identification procedure based on the maximum likelihood method, which provides results representing the degradation trend on a timescale of 10 3 h. The link function takes the form of an empirical function, which describes how operating parameters affect the degradation and is easy to integrate with control designs. The existence of the link function is proven on the varying-load experiment datasets of two flat-chip SOFCs because it statistically improves the prediction accuracy and stability compared with a constant degradation speed model. Furthermore, the effectiveness of the proposed identification procedure for time-varying degradation behaviors on the timescale of 10 4 h is also validated with 30, 000-h simulation datasets. Highlights: Accurate degradation models are built, considering degradation nonuniformity. The model form is preferred by operation control/optimization applications. 1700-h varying-load degradationAbstract: Prognostic is a potential tool for improving the durability of solid oxide fuel cells (SOFCs), which usually involves building a degradation model for prediction. However, the existing degradation models based on parallel constant operation datasets are inaccurate for integration with operation optimization and control problems of SOFCs under varying-load operation due to the nonuniform degradation behaviors. To address this issue, a link function degradation model is proposed, and its parameters are identified online with a cyclic batch identification procedure based on the maximum likelihood method, which provides results representing the degradation trend on a timescale of 10 3 h. The link function takes the form of an empirical function, which describes how operating parameters affect the degradation and is easy to integrate with control designs. The existence of the link function is proven on the varying-load experiment datasets of two flat-chip SOFCs because it statistically improves the prediction accuracy and stability compared with a constant degradation speed model. Furthermore, the effectiveness of the proposed identification procedure for time-varying degradation behaviors on the timescale of 10 4 h is also validated with 30, 000-h simulation datasets. Highlights: Accurate degradation models are built, considering degradation nonuniformity. The model form is preferred by operation control/optimization applications. 1700-h varying-load degradation experiment datasets of two cells are obtained. The existence of the link function is proved on the experiment datasets. The modeling procedure adapts to time-varying degradation characteristics. … (more)
- Is Part Of:
- International journal of hydrogen energy. Volume 47:Number 4(2022)
- Journal:
- International journal of hydrogen energy
- Issue:
- Volume 47:Number 4(2022)
- Issue Display:
- Volume 47, Issue 4 (2022)
- Year:
- 2022
- Volume:
- 47
- Issue:
- 4
- Issue Sort Value:
- 2022-0047-0004-0000
- Page Start:
- 2622
- Page End:
- 2646
- Publication Date:
- 2022-01-12
- Subjects:
- Solid oxide fuel cell -- Degradation model -- Link function -- Varying-load operation -- Prognostics
Hydrogen as fuel -- Periodicals
Hydrogène (Combustible) -- Périodiques
Hydrogen as fuel
Periodicals
665.81 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03603199 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.ijhydene.2021.10.177 ↗
- Languages:
- English
- ISSNs:
- 0360-3199
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4542.290000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 20368.xml