Prediction of oxygen utilization and purge strategy optimization for proton exchange membrane fuel cell using an Artificial Neural Network approach

Data from experiments and MATLAB code for predicting oxygen utilization in an oxygen–hydrogen proton exchange membrane fuel cell.
Experimental data were used to train the ANN model under various purge operations (including purge interval and purge duration) and load levels. Several experimental data were used to validate the model. Additionally, the MATLAB code was used to predict oxygen utilization at new purge durations and to evaluate the model’s performance.