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首页> 外文会议>ASME International Conference on Fuel Cell Science, Engineering and Technology Conference >DYNAMIC MODELING OF A REFORMED METHANOL FUEL CELL SYSTEM USING EMPIRICAL DATA AND ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM MODELS
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DYNAMIC MODELING OF A REFORMED METHANOL FUEL CELL SYSTEM USING EMPIRICAL DATA AND ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM MODELS

机译：使用经验数据和自适应神经模糊推理系统模型的重整甲醇燃料电池系统的动态建模

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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.
机译：在这项工作中，由Serenergy生产的H3-350重整甲醇燃料电池（RMFC）独立电池充电器的动态Matlab Simulink模型是在理论和经验方法的基础上开发的。 RMFC系统的优点是它们使用液体甲醇作为燃料而不是气态氢，这是难以和耗能的存储和运输。该模型包括系统各个组件的热平衡模型。在组件之间的气体流动的加热和冷却的模型也是建模的，并实施了改进过程的自适应神经模糊推理系统模型。制造用于燃料电池的鼓风机的冷却流的模型和为改装器提供工艺热量的燃烧器。这两个鼓风机具有共同排气，这意味着两个鼓风机会影响彼此的输出。模型使用经验方法考虑到这一点。使用经验方法开发了空气冷却效果的鳍效率模型。还基于标准模型实现燃料电池模型，该标准模型适于适合H3-350模块的测量性能。模型的所有各个部件通过一系列实验进行验证和微调，并且发现具有0.4％和6.4％之间的平均值误差，但通常低于3％。在组合模型的性能和实验设置之间进行比较之后，该模型被认为是对控制设计和优化目的有效。

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