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Updated: Nov 18, 2025

On the Preparation and Testing of Fuel Cell Catalysts Using the Thin Film Rotating Disk Electrode Method

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Published on: March 16, 2018

Long-term dynamic durability test datasets for single proton exchange membrane fuel cell.

Jian Zuo¹, Hong Lv¹, Daming Zhou²

¹Clean Energy Automotive Engineering Center and School of Automotive Studies, Tongji University, Shanghai 201804, China.

|February 8, 2021

Summary

This dataset captures proton exchange membrane fuel cell (PEMFC) durability under dynamic load cycles. It enables studying degradation and building predictive models for fuel cell performance.

Keywords:

Degradation Dynamic durability test Polarization test Prediction models Proton exchange membrane fuel cell

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A Guide to Concentration Alternating Frequency Response Analysis of Fuel Cells

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Published on: December 11, 2019

Area of Science:

Electrochemistry
Materials Science
Energy Systems

Background:

Proton exchange membrane fuel cells (PEMFCs) are crucial for clean energy.
Understanding long-term durability and degradation is vital for PEMFC commercialization.
Dynamic load conditions significantly impact fuel cell performance and lifespan.

Purpose of the Study:

To present a comprehensive dataset of long-term dynamic durability and polarization characterization tests for a single PEMFC.
To provide data for analyzing fuel cell degradation under realistic operating conditions.
To facilitate the development of predictive models for fuel cell performance and longevity.

Main Methods:

Utilized a Greenlight 20 test station for dynamic durability and polarization tests.
Adapted the European harmonized test protocol to create fuel cell dynamic load test cycles (FC-DLC).
Conducted a 1008-hour durability test comprising 3076 FC-DLC cycles, with periodic polarization characterizations at 100-hour intervals.

Main Results:

Recorded extensive data including dynamic load durability and polarization characteristics.
Observed and documented the output voltage degradation trend over the test duration.
Generated polarization curves at various stages to assess performance changes.

Conclusions:

The dataset offers valuable insights into PEMFC degradation mechanisms under dynamic load.
This data can be directly applied to train and validate various fuel cell predictive models.
Facilitates further research into enhancing the durability and reliability of PEMFC technology.