TY - JOUR
T1 - Artificial intelligence-based multi-objective optimisation for proton exchange membrane fuel cell
T2 - a literature review
AU - Feng, Zhiming
AU - Huang, Jian
AU - Jin, Shan
AU - Wang, Guanqi
AU - Chen, Yi
N1 - Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2022/2/1
Y1 - 2022/2/1
N2 - Proton exchange membrane fuel cells (PEMFCs) are promising devices for converting chemical energy into electrical energy due to their versatile properties, such as high power density, quick start-up, lower operating temperature, portability, etc. For PEMFC technology to outperform the incumbent technologies, artificial intelligence (AI) based multi-objective optimisation (AI-MOO) has been employed to facilitate the design and applications of PEMFC since AI-MOO is flexible enough to consider various factors simultaneously in the customized multiple objective functions and under new or updated case situations. This review provides a comprehensive literature survey on AI-MOO employed in the PEMFC field. Firstly, AI-MOO were introduced in detail, including the definition, categories and framework. Then the objectives, intelligent algorithms and trade-off methods commonly used in PEMFC were tabularised and evaluated. The application of AI-MOO in PEMFC was summarised systematically based on the application areas, including the PEMFC components, kinetics and thermodynamics, control and monitoring systems, the overall performance, and the hybrid systems. The related studies were tabularised and discussed, especially algorithms, variables, objectives and optimisation results. Finally, this review addressed the current challenges in the research area and proposed research implications for future investigations.
AB - Proton exchange membrane fuel cells (PEMFCs) are promising devices for converting chemical energy into electrical energy due to their versatile properties, such as high power density, quick start-up, lower operating temperature, portability, etc. For PEMFC technology to outperform the incumbent technologies, artificial intelligence (AI) based multi-objective optimisation (AI-MOO) has been employed to facilitate the design and applications of PEMFC since AI-MOO is flexible enough to consider various factors simultaneously in the customized multiple objective functions and under new or updated case situations. This review provides a comprehensive literature survey on AI-MOO employed in the PEMFC field. Firstly, AI-MOO were introduced in detail, including the definition, categories and framework. Then the objectives, intelligent algorithms and trade-off methods commonly used in PEMFC were tabularised and evaluated. The application of AI-MOO in PEMFC was summarised systematically based on the application areas, including the PEMFC components, kinetics and thermodynamics, control and monitoring systems, the overall performance, and the hybrid systems. The related studies were tabularised and discussed, especially algorithms, variables, objectives and optimisation results. Finally, this review addressed the current challenges in the research area and proposed research implications for future investigations.
KW - algorithms
KW - artificial intelligence (AI)
KW - multi-objective optimisation (MOO)
KW - proton exchange membrane fuel cells (PEMFCs)
UR - http://www.scopus.com/inward/record.url?scp=85119907828&partnerID=8YFLogxK
UR - https://data.ncl.ac.uk/
U2 - 10.1016/j.jpowsour.2021.230808
DO - 10.1016/j.jpowsour.2021.230808
M3 - Article
AN - SCOPUS:85119907828
SN - 0378-7753
VL - 520
JO - Journal of Power Sources
JF - Journal of Power Sources
M1 - 230808
ER -