Internal Characterization-Based Prognostics for Micro-Direct-Methanol Fuel Cells under Dynamic Operating Conditions

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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  • Dacheng Zhang
  • Xinru Li
  • Wei Wang
  • Zhengang Zhao

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Original languageEnglish
Article number4217
Journal / PublicationSensors
Issue number11
Online published1 Jun 2022
Publication statusPublished - Jun 2022



Micro-direct-methanol fuel cells (μDMFCs) use micro-electro mechanical system (MEMS) technology, which offers high energy density, portable use, quick replenishment, and free fuel reforming and purification. However, the μDMFC is limited by a short effective service life due to the membrane electrode's deterioration in electrochemical reactions. This paper presents a health status assessment and remaining useful life (RUL) prediction approach for μDMFC under dynamic operating conditions. Rather than making external observations, an internal characterization is used to describe the degradation indicator and to overcome intrusive influences in operation. Then, a Markov-process-based usage behavior prediction mechanism is proposed to account for the randomness of real-world operation. The experimental results show that the proposed degradation indicator alleviates the reduction in μDMFC output power degradation behavior caused by the user loading profile. Compared with the predictions of RUL using traditional external observation, the proposed approach achieved superior prognostic performance in both accuracy and precision.

Research Area(s)

  • micro-direct-methanol fuel cell, internal characterization, prognostics, operating conditions, remaining useful life, MEMBRANE, DEGRADATION, STATE, PERFORMANCE, PREDICTION, ELECTRODE, MODELS, MEA

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