Scope
Experimental characterization
Synchronized measurement of PEMFC stack voltage, electrical load current, fuel-cell temperature, hydrogen pressure, hydrogen temperature, and hydrogen flow during controlled electrical loading.
Model-development workflow
MATLAB-based feature processing, neural-network training/validation, and live data pathways connecting experimental DAQ streams to model evaluation.
Automation
The test platform evolved beyond passive logging into software-driven characterization.
- Integrated Arduino-based and MATLAB/NI data-acquisition pathways.
- Implemented software control of the programmable load generator and Omega hydrogen-flow instrumentation.
- Developed automated operating sequences for repeatable model-characterization runs.
- Used synchronized multisensor datasets to support regression, validation, and neural-network development.
Related ASEC 2026 Work
Accepted Presentation
Experimental Multisensor Characterization of a Proton Exchange Membrane Fuel Cell System Under Dynamic Electrical Loading
The accepted work reports 12,906 synchronized samples across seven load plateaus and a mean stack-voltage/current linear-fit slope of -1.117 V/A with R² = 0.969.
Public Disclosure Scope
This page intentionally describes the research at a systems level. Model weights, detailed neural-network architecture parameters, unpublished source code, and other implementation details are not published here.