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.

预计聚合物电解质燃料电池汽车将降低井到轮的能耗，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车已经证明了客户期望的所有性能属性，例如远距离，快速重新燃烧和冷启动。但是，燃料电池仍然太昂贵了，无法成功进行商业化。燃料电池成本的主要因素之一是燃料电池电极内使用的铂金。 实验研究表明，功能分级和微观结构的电极为减少燃料电池铂载荷的绝佳机会而不会产生负面影响。但是，燃料电池电极是几个微米厚的。因此，需要数学模型来了解电极内部发生的物理过程以改善其设计。大多数电极数学模型将电极视为宏观均匀层，因此无法适当考虑电极中局部中尺度大规模传输损失。 拟议的研究将开发重建和网格划分算法以及数学模型，以更准确地研究异质和结构工程电极中发生的中尺度质量传输和电化学反应。由于这些新型电极将需要与燃料电池中的其他组件集成，并且这种组件会影响电极的水，热和反应物平衡，因此还将研究整合中尺度和宏观燃料电池模型的数值多尺度方法。 中尺度和多尺度型号将用于功能分级电极的计算机辅助设计。这些电极将进行制造和测试，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层次结构化的电极。最成功的电极将集成在其下一代燃料电池车中。当前的项目还将有助于培训六名高素质的人员。