Air supply system, as a crucial subsystem of proton exchange membrane fuel cells (PEMFC), plays a very significant role in the efficiency and the reliability of the system. In order to better control the air supply subsystem, an appropriate model needs to be established to describe the subsystem covering whole working conditions from PEMFC startup to shutdown. This paper propose a linearized parameter varying (LPV) model based on system identification. To describe the subsystem in different working conditions, the subsystem is identified near 7 equilibrium points. Identification results show that the subsystem can be described as several linear models near equilibrium points. Based on these linear models, a LPV model is proposed solving 2‐D interpolation problem. It is proved theoretically that LPV system has the same steady‐state character and linear model at equilibrium points with identification models. The simulation and experiments results also verify that the LPV model can cover the working conditions from PEMFC startup to shutdown with accuracy both in dynamic condition and steady state.

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The durability and output performance of a fuel cell is highly influenced by the internal humidity, while in most developed models of open-cathode proton exchange membrane fuel cells (OC-PEMFC) the internal water content is viewed as a fixed value. Based on mass and energy conservation law, mass transport theory and electrochemistry principles, the model of humidity dynamics for OC-PEMFC is established in Simulink® environment, including the electrochemical model, mass flow model and thermal model. In the mass flow model, the water retention property and oxygen transfer characteristics of the gas diffusion layer is modelled. The simulation indicates that the internal humidity of OC-PEMFC varies with stack temperature and operating conditions, which has a significant influence on stack efficiency and output performance. In order to maintain a good internal humidity state during operation, this model can be used to determine the optimal stack temperature and for the design of a proper control strategy.

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