Computer-aided design of catalyst layers for polymer electrolyte fuel cells

聚合物电解质燃料电池催化剂层的计算机辅助设计

• 批准号: 445887-2012
• 负责人: SecanellGallart, Marc
• 金额: $ 7.5万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=575091
• 关键词: Computer; aided; design; catalyst; layers

Polymer electrolyte fuel cell vehicles are anticipated to lower well-to-wheel energy consumption, and reduce emissions of green house gases and other air pollutants. The current generation of fuel cell vehicles have demonstrated all the performance attributes that customers expect, such as long range, fast re-fuelling and cold start. However, the fuel cells are still too costly to enable its successful commercialization. One of the major contributors to fuel cell costs is the platinum used inside the fuel cell electrodes. Experimental research has shown that functionally-graded and micro-structured electrodes present a great opportunity to reduce fuel cell platinum loading without negatively impacting performance. Fuel cell electrodes however are several micro-meters thick; therefore, mathematical models are required to understand the physical process occurring inside the electrode in order to improve their design. Most electrode mathematical models treat the electrode as a macro-homogeneous layer, thereby not appropriately accounting for local meso-scale mass transport losses in the electrodes. The proposed research will develop reconstruction and meshing algorithms, and mathematical models to more accurately study the meso-scale mass transport and electrochemical reactions occurring in heterogeneous and structurally engineered electrodes. Since these novel electrodes will need to be integrated with the other components in a fuel cell and such components affect the water, thermal and reactant balance of the electrode, numerical multi-scale methods that integrate meso-scale and macro-scale fuel cell models will also be studied. Meso-scale and multi-scale models will be used for computer-aided design of functionally-graded electrodes. These electrodes will be fabricated and tested to assess the validity of the analysis and design framework. AFCC will also use the proposed multi-scale mathematical models to develop novel hierarchically structured electrodes. The most successful electrodes will be integrated in their next generation fuel cell vehicles. The current project will also contribute to the training of six highly qualified personnel.

聚合物电解质燃料电池汽车预计将降低整车能耗，并减少温室气体和其他空气污染物的排放。当前一代的燃料电池汽车已经展示了客户期望的所有性能属性，如续航里程长、快速加油和冷启动。然而，燃料电池仍然过于昂贵，无法实现其成功的商业化。燃料电池成本的主要贡献者之一是燃料电池电极内使用的铂。 实验研究表明，功能梯度和微结构电极为在不影响性能的情况下降低燃料电池的铂负载提供了很好的机会。然而，燃料电池电极有几个微米厚；因此，需要数学模型来了解电极内部发生的物理过程，以便改进它们的设计。大多数电极数学模型将电极视为宏观均质层，因此不能适当地考虑电极中的局部中观质量传输损失。 拟议的研究将开发重建和网格化算法，以及数学模型，以更准确地研究非均相和结构工程电极中发生的介观质量传输和电化学反应。由于这些新型电极需要与燃料电池中的其他组件集成在一起，并且这些组件影响电极的水、热和反应物平衡，因此还将研究整合中观和宏观燃料电池模型的多尺度数值方法。 细观和多尺度模型将用于功能梯度电极的计算机辅助设计。这些电极将被制造和测试，以评估分析和设计框架的有效性。AFCC还将使用所提出的多尺度数学模型来开发新型的分层结构电极。最成功的电极将被集成到他们的下一代燃料电池汽车中。目前的项目还将有助于培训六名高素质人员。