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

IF 4.9 3区计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY

Journal of Bionic Engineering Pub Date : 2024-11-18 DOI:10.1007/s42235-024-00607-2

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

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Abstract

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.

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人工智能辅助质子交换膜燃料电池流场设计：进展与展望

双极板是质子交换膜燃料电池（PEMFC）的关键部件之一，合理的双极板流场设计将提高电池的性能。在此，我们回顾了传统的和仿生的流场设计在最近的文献中，重点是仿生流场。特别地，将仿生流场归纳为植物型和动物型两种类型。传统的流场设计方法基于经验和试错法，需要花费更多的时间来找到最优的流场。近年来，由于机器学习具有良好的预测和优化能力，被用于优化双极板的流场结构。本文将人工智能辅助流场设计分为单目标优化和多目标优化两类。此外，对人工智能辅助流场设计进行了威胁-机会-劣势-优势（tow）分析。人工智能可以为解决复杂的仿生流场设计问题提供强大的工具，并显著提高具有仿生流场的PEMFC的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Bionic Engineering 工程技术-材料科学：生物材料

CiteScore

7.10

自引率

10.00%

发文量

162

审稿时长

10.0 months

期刊介绍： The Journal of Bionic Engineering (JBE) is a peer-reviewed journal that publishes original research papers and reviews that apply the knowledge learned from nature and biological systems to solve concrete engineering problems. The topics that JBE covers include but are not limited to: Mechanisms, kinematical mechanics and control of animal locomotion, development of mobile robots with walking (running and crawling), swimming or flying abilities inspired by animal locomotion. Structures, morphologies, composition and physical properties of natural and biomaterials; fabrication of new materials mimicking the properties and functions of natural and biomaterials. Biomedical materials, artificial organs and tissue engineering for medical applications; rehabilitation equipment and devices. Development of bioinspired computation methods and artificial intelligence for engineering applications.