Real-Time Capable Transient H2 Partial Pressure Model for Proton Exchange Membrane Fuel Cell Systems

Q3 Engineering

IFAC-PapersOnLine Pub Date : 2025-01-01 DOI:10.1016/j.ifacol.2025.03.003

Martin Osterhammer , Fengmin Du , Volker Formanski , Marcelo Lobo Heldwein

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引用次数: 0

Abstract

Fuel cell electric vehicles hold a significant promise for reducing the carbon footprint in the automotive sector by leveraging H₂ as a clean fuel source. Maintaining a consistent H₂ supply to the fuel cell system is vital. N₂ crossover can lead to an inert gas built-up on the H₂ supply side, adversely affecting fuel cell performance and durability. Through purging, gases are released, and a N₂ built-up in the H₂ supply system can be prevented, yet this also leads to fuel loss. This fuel loss can be minimized by keeping an optimal N₂ molar fraction. We developed a dynamic model for effectively designing, controlling, and diagnosing fuel cell systems by predicting the N₂ molar fraction in the H₂ supply. This model considers factors such as N₂ distribution throughout the fuel cell stack, N₂ crossover, and the purge process. The model is simplified to a differential equation of first order and solved using the explicit Euler method at a typical automotive time step of 0.01s. The proposed model is validated by a H₂ measurement in a fuel cell system with passive recirculation.

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质子交换膜燃料电池系统的实时瞬时H2分压模型

燃料电池电动汽车通过利用氢气作为清洁燃料来源，在减少汽车行业的碳足迹方面具有重要的前景。维持燃料电池系统持续的氢气供应至关重要。N2交叉会导致惰性气体积聚在H2供应侧，对燃料电池的性能和耐用性产生不利影响。通过吹扫，气体被释放，可以防止H2供应系统中积聚的N2，但这也会导致燃料损失。这种燃料损失可以通过保持最佳的N2摩尔分数来最小化。我们开发了一个动态模型，通过预测H2供应中的N2摩尔分数来有效地设计、控制和诊断燃料电池系统。该模型考虑了N2在整个燃料电池堆中的分布、N2交叉和吹扫过程等因素。将模型简化为一阶微分方程，采用显式欧拉法在典型的汽车时间步长为0.01s时求解。通过对无源再循环燃料电池系统H2的测量，验证了该模型的有效性。

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来源期刊

IFAC-PapersOnLine Engineering-Control and Systems Engineering

CiteScore

1.70

自引率

0.00%

发文量

1122

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