Operating conditions combination analysis method of optimal water management state for PEM fuel cell
Journal article, 2023

The water content of proton exchange membrane fuel cells (PEMFCs) affects the transport of reactants and the conductivity of the membrane. Effective water management measures can improve the performance and extend the lifespan of the fuel cell. The water management state of the stack is influenced by various external operating conditions, and optimizing the combination of these conditions can improve the water management state within the stack. Considering that the stack's internal resistance can reflect its water management state, this study first establishes an internal resistance-operating condition model that considers the coupling effect of temperature and humidity to determine the variation trend of total resistance and stack humidity with single-factor operating conditions. Subsequently, the water management state optimization method based on the ANN-HGPSO algorithm is proposed, which not only quantitatively evaluates the influence weights of different operating conditions on the stack's internal resistance but also efficiently and accurately obtains the optimal combination of five operating conditions: working temperature, anode gas pressure, cathode gas pressure, anode gas humidity, and cathode gas humidity to achieve the optimal water management state in the stack, within the entire range of current densities. Finally, the response surface experimental results of the stack also validate the effectiveness and accuracy of the ANN-HGPSO algorithm. The method mentioned in this article can provide effective strategies for efficient water management and output performance optimization control of PEMFC stacks.

Water management statue

Response surface method

PEMFC

Operating condition optimization

Internal resistance-operating condition model

Author

Wenxin Wan

Wuhan University of Technology

Yang Yang

Wuhan University of Technology

Yang Li

Chalmers, Electrical Engineering, Systems and control

Changjun Xie

Wuhan University of Technology

Jie Song

Global Energy Interconnection Research Institute Co. Ltd., Beijing

Zhanfeng Deng

Global Energy Interconnection Research Institute Co. Ltd., Beijing

Jinting Tan

State Key Laboratory of Advanced Technology for Materials Synthesis and Processing

Ruiming Zhang

Wuhan University of Technology

Green Energy and Intelligent Transportation

20972512 (ISSN) 27731537 (eISSN)

Vol. 2 4 100105

Subject Categories

Energy Engineering

Control Engineering

DOI

10.1016/j.geits.2023.100105

More information

Latest update

7/24/2023