Dynamic temperature model for proton exchange membrane fuel cell using online variations in load current and ambient temperature
This paper presents a dynamic temperature model for a proton exchange membrane fuel cell (PEMFC) system. The proposed model overcomes the complexity of conventional models using first-order expressions consisting of load current and ambient temperature. The proposed model also incorporates a PEMFC cooling system, which depends upon the temperature difference between events. A dynamic algorithm is developed to detect load changing events and calculate instantaneous PEMFC temperature variations. The parameters of the model are extracted by employing the lightning search algorithm (LSA). The temperature characteristics of the NEXA 1.2 kW PEMFC system are experimentally studied to validate model performance. The results show that the proposed model output and the temperature data obtained from experiments for linear and abrupt changes in PEMFC load current are in agreement. The root-mean-square error between the model output and experimental results is less than 0.9. Moreover, the proposed model outperforms the conventional models and provides advantages such as simplicity and adaptability for low and high sampling data rates of input variables, namely, load current and ambient temperature. The model is not only helpful for simulations but also suitable for dynamic real-time controllers and emulators.