AI-Assisted Flow Field Design for Proton Exchange Membrane Fuel Cells:Progress and Perspective  

作　　者：Tongxi Zheng Fanyu Meng Wenxuan Fan Mingxin Liu Dafeng Lu Yang Luan Xunkang Su Guolong Lu Zhenning Liu 

机构地区：[1]Key Laboratory of Bionic Engineering(Ministry of Education),College of Biological and Agricultural Engineering,Jilin University,Changchun,130022,China [2]Product Planning and Project Management Department,China FAW Group Corporation Limited,Changchun,130011,China

出　　处：《Journal of Bionic Engineering》2025年第1期47-64,共18页仿生工程学报(英文版)

基　　金：supported by the National Natural Science Foundation of China(52075214and 51975245);the National Key R&D Program of China(No.2022YFE0138500);Jilin Provincial Science&Technology Department(20220201115GX);Key Science and Technology R&D Projects of Jilin Province(2020C023-3);Program of Jilin University Science and Technology Innovative Research Team(2020TD-03);the Fundamental Research Funds for the Central Universities.

摘　　要：Bipolar plate is one of the key components of Proton Exchange Membrane Fuel Cell(PEMFC)and a reasonable flow field design for bipolar plate will improve cell performance.Herein,we have reviewed conventional and bionic flow field designs in recent literature with a focus on bionic flow fields.In particular,the bionic flow fields are summarized into two types:plant-inspired and animal-inspired.The conventional methodology for flow field design takes more time to find the optimum since it is based on experience and trial-and-error methods.In recent years,machine learning has been used to optimize flow field structures of bipolar plates owing to the advantages of excellent prediction and optimization capability.Artificial Intelligence(AI)-assisted flow field design has been summarized into two categories in this review:single-objective optimization and multi-objective optimization.Furthermore,a Threats-Opportunities-Weaknesses-Strengths(TOWS)analysis has been conducted for AI-assisted flow field design.It has been envisioned that AI can afford a powerful tool to solve the complex problem of bionic flow field design and significantly enhance the performance of PEMFC with bionic flow fields.

关 键 词：Proton exchange membrane fuel cell Artificial intelligence BIONIC Flow field Algorithm 

分 类 号：TM911.4[电气工程—电力电子与电力传动]