Dynamic Modeling of a Reformed Methanol Fuel Cell System using Empirical Data and Adaptive Neuro-Fuzzy Inference System Models

Kristian Kjær Justesen, Søren Juhl Andreasen, Hamid Reza Shaker

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

4 Citations (Scopus)

Abstract

In this work, a dynamic MATLAB Simulink model of a H3-350 Reformed Methanol Fuel Cell (RMFC) stand-alone battery charger produced by Serenergy is developed on the basis of theoretical and empirical methods. The advantage of RMFC systems is that they use liquid methanol as a fuel instead of gaseous hydrogen, which is difficult and energy consuming to store and transport. The models include thermal equilibrium models of the individual components of the system. Models of the heating and cooling of the gas flows between components are also modeled and Adaptive Neuro-Fuzzy Inference System models of the reforming process are implemented. Models of the cooling flow of the blowers for the fuel cell and the burner which supplies process heat for the reformer are made. The two blowers have a common exhaust, which means that the two blowers influence each other’s output. The models take this into account using an empirical approach. Fin efficiency models for the cooling effect of the air are also developed using empirical methods. A fuel cell model is also implemented based on a standard model which is adapted to fit the measured performance of the H3-350 module. All the individual parts of the model are verified and fine-tuned through a series of experiments and are found to have mean absolute errors between 0.4% and 6.4% but typically below 3%. After a comparison between the performance of the combined model and the experimental setup, the model is deemed to be valid for control design and optimization purposes.
Original languageEnglish
Title of host publicationProceedings of the ASME 2013 11th International Conference on Fuel Cell Science, Engineering and Technology Conference
Number of pages11
PublisherAmerican Society of Mechanical Engineers
Publication date2013
Article numberV001T04A005
ISBN (Print)978-0-7918-5552-2
DOIs
Publication statusPublished - 2013
EventASME 2013 11th Fuel Cell Science, Engineering and Technology Conference - Boston, United States
Duration: 14 Jul 201319 Jul 2013

Conference

ConferenceASME 2013 11th Fuel Cell Science, Engineering and Technology Conference
CountryUnited States
CityBoston
Period14/07/201319/07/2013

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    Justesen, K. K., Andreasen, S. J., & Shaker, H. R. (2013). Dynamic Modeling of a Reformed Methanol Fuel Cell System using Empirical Data and Adaptive Neuro-Fuzzy Inference System Models. In Proceedings of the ASME 2013 11th International Conference on Fuel Cell Science, Engineering and Technology Conference [V001T04A005 ] American Society of Mechanical Engineers. https://doi.org/10.1115/FuelCell2013-18110