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Modeling-based portrait and intelligent diagnostics of polymer electrolyte fuel cells

Modeling-based portrait and intelligent diagnostics of polymer electrolyte fuel cells
基于建模的聚合物电解质燃料电池画像与智能诊断
批准号:
513543-2017
负责人:
Gates, Byron
金额:
$7.58万
依托单位:
依托单位国家:
加拿大
项目类别:
Collaborative Research and Development Grants
财政年份:
2019
资助国家:
加拿大
项目状态:
已结题
起止时间:
2019-01-01 至 2020-12-31

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中文摘要
翻译
这一应用促进了聚合物电解质燃料电池(PEFC)的建模和诊断方面的协调策略,PEFC被吹捧为运输和固定电力的能量转换设备。绿光创新公司(GI)是一家为汽车原始设备制造商和研究实验室提供燃料电池测试设备的领先供应商,在全球拥有700多个运营站点。为了支持这一地位,本文提出的诊断平台将对被测设备(DUT)的健康状态提供快速、可靠、准确和自主的评估,并实时分析其对不断变化的运行条件和负载的响应。基于模型的工具将把性能的变化与细胞组件的结构和属性的变化联系起来,以破译性能影响的机制起源。此外,还将设计诊断工具,以预测操作故障并使其原因合理化。这套功能将对指导未来材料研究和电池和堆栈设计的方向至关重要;它将使开发人员能够设计故障缓解和恢复策略。作为这一平台的基础,SFU团队将开发物理-数学模型,以绘制PEFC的全面性能画像。利用这幅肖像,该小组将开发测试算法和协议,并与GI的合作伙伴密切互动。GI将把诊断方法和工具集成到其控制和自动化软件Emerald中。UBC的片上系统研究实验室将为大型燃料电池组的测试开发特定的电子硬件。
英文摘要
This application fosters a concerted strategy in modeling and diagnostics of polymer electrolyte fuel cells (PEFCs), which are touted as energy conversion devices for transportation and stationary power. Greenlight Innovation Corp. (GI) is a leading supplier of fuel cell testing equipment to automotive OEMs and research labs with over 700 stations in operation worldwide. To bolster this position, the diagnostics platform proposed herein is to provide quick, reliable, accurate and autonomous assessment of the state of health of the Device Under Test (DUT) and analyze, in real time, its response to changing operating conditions and load. Model-based tools will correlate changes in performance with variations in structure and properties of cell components, to decipher the mechanistic origins of performance effects. Furthermore, diagnostic tools will be devised to predict operational failures and rationalize their causes. The suite of capabilities will be essential to steer future directions in materials research and design of cells and stacks; it will enable developers to engineer failure mitigation and recovery strategies. As the basis for this platform, the SFU team will develop physical-mathematical models to draw a comprehensive performance portrait of PEFCs. Using this portrait, the group will develop testing algorithms and protocols, closely interacting with partners at GI. GI will integrate diagnostic methods and tools into Emerald, its control and automation software. The system-on-a-chip research lab at UBC will develop specific electronics hardware for tests on large fuel cell stacks.
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Tuning the Surface Chemistry of Structured Materials for Enhanced Performance
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  • 项目类别:
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Modeling-based portrait and intelligent diagnostics of polymer electrolyte fuel cells
  • 批准号:
    513543-2017
  • 项目类别:
    Collaborative Research and Development Grants
  • 资助金额:
    $7.58万
  • 财政年份:
    2020
  • 负责人:
    Gates, Byron
  • 依托单位:
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