Dynamic semiempirical PEMFC model for prognostics and fault diagnosis

Saad Saleem Khan, Hussain Shareef, Mohsen Kandidayeni, Loic Boulon, Abbou Amine, El Hasnaoui Abdennebi

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)


This article 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.

Original languageEnglish
Article number9316245
Pages (from-to)10217-10227
Number of pages11
JournalIEEE Access
Publication statusPublished - 2021


  • Fault diagnostics
  • optimization
  • prognostics
  • statistical analysis

ASJC Scopus subject areas

  • General Computer Science
  • General Materials Science
  • General Engineering


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