Reliability computing of polymer-electrolyte-membrane fuel cell stacks through Petri nets

Wieland, Christoph Martin; Schmid, O.; Meiler, M.; Wachtel, A.; Linsler, Dominic

doi:10.1016/j.jpowsour.2008.10.010

Cited by 21 publications

(18 citation statements)

References 14 publications

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“…The Petri net is a very well suited methodology to model complex systems with true concurrency and dependencies. To the best of the authors' knowledge the only research contribution featuring the use of Petri nets for computing fuel cells reliability is given in [8]. However, while the model in [8] considers the reliability of the stack only, in the paper presented here, the boundaries of the model are extended to include the balance of the plant.…”

Section: Literature Reviewmentioning

confidence: 99%

“…To the best of the authors' knowledge the only research contribution featuring the use of Petri nets for computing fuel cells reliability is given in [8]. However, while the model in [8] considers the reliability of the stack only, in the paper presented here, the boundaries of the model are extended to include the balance of the plant. The model simulates the operation of the fuel cell stack and its supporting system to predict the system performance based on the system structure and the component's deterioration processes.…”

Section: Literature Reviewmentioning

confidence: 99%

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Performance modelling of fuel cell systems through Petri nets

Fecarotti

Andrews

2016

2016 Annual Reliability and Maintainability Symposium (RAMS)

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This paper introduces a model based on the Petri net method for the performance evaluation of fuel cell systems during operation. The model simulates the operation of the fuel cell stack and its supporting systems by taking into account the causal relationships between the operation of the balance of plant and the fuel cell stack performance. Failures of the supporting system affect the operating parameters such as the stack temperature and humidity, the reactants' flow and pressure, and, in turn, the stack performance in terms of output voltage. Voltage degradation rates are needed in order to evaluate the system lifetime. The voltage degradation is related to the important operating parameters by means of empirical relationships. In order to demonstrate the capability of the model, numerical simulations are performed using data for voltage degradation rates collected from the literature. The voltage decay rate is modelled as a random variable within the aforementioned ranges. Time to failure and time to repair of components are generated from stochastic distributions. The use of a stochastic approach allows taking into account data uncertainty and variability. The modelling process produces distributions of the output parameters rather than point estimates delivered by alternative methods. This enables an appreciation of the best and worst possible output lifetime as well as the expected system performance. The model can be used to support the design, operation and maintenance of fuel cell systems.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Performance modelling of fuel cell systems through Petri nets

Fecarotti

Andrews

2016

2016 Annual Reliability and Maintainability Symposium (RAMS)

View full text Add to dashboard Cite

show abstract

“…There is currently only one example of Petri-Net use for reliability analysis of PEMFCs from Wieland, et al [13] and is a good start to develop reliability analysis in this field. However, the model could be further developed to accurately represent all of the previously identified failure modes from FMEA and FTA work presented by Whiteley, et al [10] [11].…”

Section: Existing Work In the Literaturementioning

confidence: 99%

“…In the work by Wieland, et al [13], degradation transition severity is calculated from a normal distribution using the Natural Aging parameter from 1 to 70 µVh −1 (microvolts per hour). This assumes that degradation is a simple process and can be derived from lifetime test degradation rates.…”

Section: Limitations With Parameters Usedmentioning

confidence: 99%