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Artificial intelligence-based multi-objective optimisation for proton exchange membrane fuel cell: a literature review
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  • Zhiming Feng ,
  • Jian Huang ,
  • Shan Jin ,
  • Guanqi Wang ,
  • Leo Chen
Zhiming Feng
Newcastle University

Corresponding Author:[email protected]

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Jian Huang
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Guanqi Wang
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Proton exchange membrane fuel cells (PEMFCs) are promising devices for conversing chemical energy into electrical energy due to their versatile properties, such as high power density, quick start-up, lower operating temperature, and 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 PEMFC field. Firstly, AI-MOO were introduced in detail, including the definition, categories and framework. Then the objectives, intelligent algorithms and trade-off methods that are commonly used in PEMFC were tabularised and evaluated. The application of AI-MOO in PEMFC were 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.
Feb 2022Published in Journal of Power Sources volume 520 on pages 230808. 10.1016/j.jpowsour.2021.230808