Power humidity temperature modelling and control of proton exchange membrane fuel cells

Effective power humidity temperature management is necessary for the safe and efficient operation of proton exchange membrane fuel cells (PEMFC). Therefore a PEMFC modeling method and an intelligent proportional integral differential (PID) control based on neural networks strategy are presented in the paper to keep the PEMFC within the ideal operation range. Firstly, a power humidity temperature mathematical model is developed based on the molar conservation principles, energy balance theory and empirical equations. Secondly, the electrical power, humidity and temperature control structure and the intelligent PID control based on neural networks technique are designed, and the neural networks identification (NNI) model is applied to acquire the plant Jacobian information. Thus the electrical power, humidity and temperature are controlled by regulating the stack current, anode inlet water flow rate and cooling air flux respectively. Finally, the physical model, NNI model and neural networks (NN) PID controllers are simulated and analyzed in Matlab/Simulink software, and the results demonstrate the effectiveness of the above means.