燃料电池数字孪生系统综述

doi:10.11949/0438-1157.20251029

摘要/Abstract

摘要：

燃料电池凭借其高效率、零排放和长寿命等优势，在可持续能源体系中的地位日益凸显。而数字孪生技术作为理论向工程转化的关键人工智能工具，提供了一个虚拟建模平台，为燃料电池的全生命周期管理提供创新解决方案。首先论述了燃料电池的发展现状、工作原理，随后解释了数字孪生系统的功能、架构和结构以及其在燃料电池领域的发展潜力。探讨了数字孪生系统在燃料电池领域的应用，分别从质子交换膜燃料电池的多物理场预测、燃料电池数字孪生的管理系统以及数字孪生系统在燃料电池剩余使用寿命预测与健康管理三方面进行总结论述。最后阐述了数字孪生系统应用于燃料电池的挑战与发展前景。

关键词: 燃料, 燃料电池, 数字孪生, 质子交换膜, 预测, 多物理场预测, 管理系统, 剩余使用寿命

Abstract:

Fuel cells are attracting increasing attention in sustainable energy systems because of their high efficiency, zero emissions, and long lifespan. Digital Twin technology, as an AI-driven enabling tool, bridges theoretical models and engineering applications by providing a virtual modeling platform. This platform supports innovative solutions for the full life-cycle management of fuel cells.This paper systematically reviews the current development and working principles of fuel cells, and presents the basic functions, architecture, and framework of digital twin systems, along with their potential applications in the fuel cell field. Furthermore, the applications of digital twin systems in fuel cells are summarized from three perspectives: (1) multi-physics prediction within proton exchange membrane fuel cells; (2) digital-twin-based fuel cell management systems; and (3) Digital Twin implementations for remaining useful life prediction and health management. Finally, the challenges and future development trends of digital twin technology for fuel cells are discussed and summarized.

Key words: fuel, fuel cells, digital twin, proton exchange membrane, prediction, multi-physics prediction, management system, remaining useful life

中图分类号:

TM911.4-1

姚晓多, 许强辉, 张文强. 燃料电池数字孪生系统综述[J]. 化工学报, DOI: 10.11949/0438-1157.20251029.

Xiaoduo YAO, Qianghui XU, Wenqiang ZHANG. An Overview of Digital Twin Systems for Fuel Cells[J]. CIESC Journal, DOI: 10.11949/0438-1157.20251029.

图/表 11

图 1 近三年中国新能源汽车月度销量[7]

Fig. 1 Monthly Sales of New Energy Vehicles in China (For the Past Three Years)[7]

表 1 FCs的主要类型［6］

Table 1 Classification of FCs［6］

	质子交换膜燃料电池（PEMFCs）	碱性燃料电池（AFCs）	磷酸燃料电池（PAFCs）	熔融碳酸盐燃料电池（MCFCs）	固体氧化物燃料电池（SOFCs）
主要应用	便携式、交通运输、小规模固定式	便携式及固定式	固定式	固定式	固定式
电解质	聚合物膜	氢氧化钾	磷酸	熔融碳酸盐	陶瓷材料
电荷载体	H⁺	OH⁻	H⁺	CO₃²⁻	O²⁻
工作温度	-40～120°C (高温PEMFCs为150～180°C)	50～200°C	150～220°C	600～700°C	500～1000°C
电效率	最高65～72%	最高70%	最高45%	最高60%	最高65%
主要燃料	氢气、重整氢气、直接甲醇燃料电池中的甲醇	氢气或裂解氨气	氢气或重整氢气	氢气、生物气或甲烷	氢气、生物气或甲烷

图 2 FCs的化学反应过程示意图[9]

Fig. 2 Schematic representation of the chemical reaction processes in FCs[9]

图 3 PEMFCs的基本结构[9]

Fig. 3 Basic Structure of PEMFCs [9]

图 4 DT的基本功能[25]

Fig. 4 Fundamental Functions of DT [25]

图 5 DT架构[25]

Fig. 5 DT Architecture[25]

图 6 闭环式DT四层结构

Fig. 6 Four-Layer Closed-Loop Architecture of DT

图 7 (a) PEMFCs模拟结构示意图；(b)阴极蛇形流道与阳极并联流道示意图，以及用于生成多物理场数据的网格节点划分[43]。图中紫色区域分别表示阴极蛇形流道与阳极并联流道的结构。

Fig. 7 (a) Schematic diagram of the simulated PEMFCs structure. (b) Schematic representation of the cathode serpentine flow field and the anode parallel flow field, along with the mesh node partition used for multi-physics field data generation[43]. The purple regions indicate the structural layouts of the cathode serpentine channel and the anode parallel channel.

表 2 HFCs管理模块［49］

Table 2 HFCs management module［49］

管理模块	核心功能	技术价值
水管理	膜电极湿度控制	避免质子传导率衰减
热管理	温度场均衡调控	防止局部热点导致的材料老化
气管理	反应物供给优化	提升氢气利用率至>98%
安全性管理	氢泄漏实时诊断	事故响应时间缩短至50ms
健康管理	数据分析	性能优化与安全保障
监控管理	多源数据融合	提供系统级决策支持

图 8 正交分解技术下液态水饱和度场的DT结果与仿真结果对比[44]

Fig. 8 DT versus Simulation of Liquid Water Saturation Field using POD Technique[44]

图 9 基于数据驱动的DT预测方法[79]

Fig. 9 Proposed data-driven DT prognostics method[79]

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