Enhancing reactant mass transfer inside fuel cells to improve dynamic performance via intelligent hydrogen pressure control. (1st September 2021)
- Record Type:
- Journal Article
- Title:
- Enhancing reactant mass transfer inside fuel cells to improve dynamic performance via intelligent hydrogen pressure control. (1st September 2021)
- Main Title:
- Enhancing reactant mass transfer inside fuel cells to improve dynamic performance via intelligent hydrogen pressure control
- Authors:
- Zeng, Tao
Zhang, Caizhi
Zhou, Anjian
Wu, Qi
Deng, Chenghao
Chan, Siew Hwa
Chen, Jinrui
Foley, Aoife M. - Abstract:
- Abstract: Due to internal mass transfer resistance, the dynamic response of fuel cells often lags the demand power in vehicular powertrains. In this study, an intelligent hydrogen pressure control method based on short-term vehicular power demand prediction is proposed to enhance mass transfer inside diffusion layer and improve dynamic performance. Sensitivity analysis confirmed the positive effect of hydrogen pressure on the dynamic response of fuel cells and revealed the necessity of adaptive switching of hydrogen pressure according to power demand. The short-term power demand is predicted using an iterative learning framework (ILF). Then, the variable-pressure control strategy is presented to realize the intelligent mode switching of hydrogen pressure according to the predicted power demand via a three-way solenoid valve. The effectiveness of the proposed method is validated experimentally. The results show that ILF achieves the best predictability for short-term power demand compared with non-iterative learning framework, thus guaranteeing high decision correctness of the prediction-based control strategy up to 99.9%. The dynamic performance of fuel cell is improved effectively, and its delivered energy increases by 6.98%, such that the battery discharge energy can be reduced by 45.4% in a 35-s test, which confirms the viability of the proposed hydrogen pressure control method. Highlights: Hydrogen mass transfer inside fuel cells is enhanced via intelligent pressureAbstract: Due to internal mass transfer resistance, the dynamic response of fuel cells often lags the demand power in vehicular powertrains. In this study, an intelligent hydrogen pressure control method based on short-term vehicular power demand prediction is proposed to enhance mass transfer inside diffusion layer and improve dynamic performance. Sensitivity analysis confirmed the positive effect of hydrogen pressure on the dynamic response of fuel cells and revealed the necessity of adaptive switching of hydrogen pressure according to power demand. The short-term power demand is predicted using an iterative learning framework (ILF). Then, the variable-pressure control strategy is presented to realize the intelligent mode switching of hydrogen pressure according to the predicted power demand via a three-way solenoid valve. The effectiveness of the proposed method is validated experimentally. The results show that ILF achieves the best predictability for short-term power demand compared with non-iterative learning framework, thus guaranteeing high decision correctness of the prediction-based control strategy up to 99.9%. The dynamic performance of fuel cell is improved effectively, and its delivered energy increases by 6.98%, such that the battery discharge energy can be reduced by 45.4% in a 35-s test, which confirms the viability of the proposed hydrogen pressure control method. Highlights: Hydrogen mass transfer inside fuel cells is enhanced via intelligent pressure control. Variable hydrogen pressure control strategy is systematically proposed. Short-term vehicular power demand is accurately predicted. Method validation is carried out experimentally through case study. … (more)
- Is Part Of:
- Energy. Volume 230(2021)
- Journal:
- Energy
- Issue:
- Volume 230(2021)
- Issue Display:
- Volume 230, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 230
- Issue:
- 2021
- Issue Sort Value:
- 2021-0230-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-09-01
- Subjects:
- Fuel cell -- Dynamic performance -- Mass transfer -- Hydrogen pressure -- Intelligent control -- Power prediction
Power resources -- Periodicals
Power (Mechanics) -- Periodicals
Energy consumption -- Periodicals
333.7905 - Journal URLs:
- http://www.elsevier.com/journals ↗
- DOI:
- 10.1016/j.energy.2021.120620 ↗
- Languages:
- English
- ISSNs:
- 0360-5442
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3747.445000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 24854.xml