Fuel Cell System Development for Heavy Duty Vehicles

Abstract

As California advances its ambitious goals for transportation electrification to combat climate change, hydrogen-powered fuel cells are emerging as a viable solution for overcoming the challenges of heavy-duty vehicles, offering an efficient alternative to lithium-ion batteries because they produce minimal chemical, thermal, and carbon emissions. One type of hydrogen fuel cell technology called proton exchange membrane fuel cells (PEMFCs) has garnered the most attention due to its distinct advantages, including relatively low operating temperatures (60–80 °C) and reliable performance at high current densities. However, despite their promise, PEMFCs face challenges, including in optimizing stack power output and safety concerns. To tackle these issues, accurate modeling and control strategies are essential. This study focuses on using data-driven modeling (specifically using a process known as “closed-loop system identification” under proportional controller and pseudo-random binary sequence excitation methods) to better understand and manage PEMFC systems. Various transfer functions models were analyzed, including first-order, first-order plus time delay, second-order, and second-order plus time delay models. The resulting closed-loop identification approach was applied on the humidifier, cooling, and oxygen supplier subsystems of simulated PEMFC to build their models under controlled operations. The results of this study highlight the potential of closed-loop system identification techniques to improve fuel cell vehicle performance in power supply, water, and heat management, without interrupting PEMFC operations. These findings demonstrate the significance of precise modeling as a cornerstone for advancing PEMFC control strategies and optimizing their application in renewable transportation and a more sustainable future.

Key findings

• ▸PEMFCs have relatively low operating temperatures (60–80 °C) and reliable performance at high current densities.
• ▸Data-driven modeling using closed-loop system identification can help better understand and manage PEMFC systems.
• ▸Transfer functions models, including first-order, first-order plus time delay, second-order, and others, were analyzed for PEMFC systems.

Keywords

Identifiers

DOI

10.31979/mti.2025.2441

Journal

Unknown journal

Year

2025