Summary This paper introduces a novel dynamic semiempirical model for the proton exchange membrane fuel cell (PEMFC). The proposed model not only considers the stack output voltage but also provides valid waveforms of component voltages, such as the no‐load, activation, ohmic, and concentration voltages of the PEMFC stack system. Experiments under no‐load, ramping load, and dynamic load conditions are performed to obtain various voltage components. According to experimental results, model parameters are optimised using the lightning search algorithm by providing valid theoretical ranges of parameters to the lightning search algorithm code. In addition, the correlation between the vapour and water pressures of the PEMFC is obtained to model the component voltages. Finally, all component voltages and the stack output voltage are validated by using the experimental/theoretical waveforms mentioned in previous research. The proposed model is also compared with a recently developed semiempirical model of PEMFC through particle swarm optimisation. The proposed dynamic model may be used in future in‐depth studies on PEMFC behaviour and in dynamic applications for health monitoring and fault diagnosis.

Proton-exchange-membrane fuel cells (PEMFCs) are a popular source of alternative energy because of their operational reliability and compactness. This paper presents an improved model to represent the semi-empirical voltage of PEMFCs to overcome the limitations of existing models. The proposed model considers variations in ambient conditions, such as the ambient temperature

No abstract

No abstract

Proton exchange membrane fuel cell is an emerging renewable energy resource for transportation and power generation. Similar to other renewable resources, the performance of proton exchange membrane fuel cell is affected by ambient conditions. However, procedures for analyzing the influences of such conditions on the performance of proton exchange membrane fuel cells are expensive and time-consuming. Moreover, the commonly used models have been developed on the basis of standard ambient conditions. Thus, these models are difficult to utilize under adverse ambient conditions. This study was performed to develop suitable proton exchange membrane fuel cell models that could reflect the effects of ambient conditions on the output voltage and current of the models. The first proposed model used the advantages of electrical and thermal relationships of a complex semiempirical model of a proton exchange membrane fuel cell. A simplified proton exchange membrane fuel cell model that used passive electrical components was then developed by central composite surface design. Both proposed models were simulated using various ambient temperatures, pressures, and load resistances by considering that the applied hydrogen pressure is known. Results showed that the output voltage of proton exchange membrane fuel cell decreased when ambient temperature increased and pressure decreased. This variation was dominant when the load resistance was reduced. Computation using the simplified model was remarkably faster than that using the first model. The proposed model can be beneficial, especially for aircraft applications and unusual ambient conditions.

No abstract

No abstract

This paper introduces a dynamic semiempirical model that predicts the degradation of a proton exchange membrane fuel cell (PEMFC) by introducing time-based terms in the model. The concentration voltage drop is calculated using a new statistical equation based on the load current and working time, whereas the ohmic and activation voltage drops are updated using time-based equations borrowed from the existing literature. Furthermore, the developed model calculates the membrane water content in the PEMFC, which indicates the membrane hydration state and indirectly diagnoses the flooding and drying faults. Moreover, the model parameters are optimized using a recently developed butterfly optimization algorithm. The model is simple and has a short runtime; therefore, it is suitable for monitoring. Voltage degradation under various loading currents was observed for long working hours. The obtained results indicate a significant degradation in PEMFC performance. Therefore, the proposed model is also useful for prognostics and fault diagnosis. INDEX TERMS Fault diagnostics, optimization, PEMFC, prognostics, statistical analysis Engineering for Smart & Sustainable Systems Research Department at Mohammadia School of Engineering (Rabat/Morocco). His scientific activities have mostly focused on fuel cells as a solution of storage of energy (more exactly, developing new methods for modeling and control of fuel cells).