Dynamic Modeling and Simulation of PEM Fuel Cells Based on BP Neural Network

The operation principles of proton exchange membrane (PEM) fuel cell system relate to thermodynamics, electrochemistry, hydrodynamics, mass transfer theory, which form a complex nonlinear system, and it is different to establish its mathematical model. This paper utilizes the approach and self-study ability of artificial neural network to build a model of nonlinear system, and adapts the modified BP to build a dynamic model of PEM fuel cell. The model makes use of the 4000 groups´ experimental data as training specimens. Current density, flow rate and pressure of air and hydrogen as inputs of the model, voltage as the output . It is helpful for improving the performance of cells and optimizing control of cells.