陈超,王硕,兰海兵,杨林林,吴私,宋学官.基于代理模型的直流道质子交换膜燃料电池优化设计[J].,2020,60(3):244-250 |
基于代理模型的直流道质子交换膜燃料电池优化设计 |
Optimization of straight flow channel for proton exchange membrane fuel cell based on surrogate model |
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DOI:10.7511/dllgxb202003004 |
中文关键词:质子交换膜燃料电池数值模拟Kriging代理模型遗传算法 |
英文关键词:proton exchange membrane fuel cell (PEMFC)numerical simulationKriging surrogate modelgenetic algorithm |
基金项目:国家自然科学基金辽宁联合基金资助项目(U1608256). |
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中文摘要: |
质子交换膜燃料电池是一种可以将储存在燃料中的化学能转化为电能的装置.应用Kriging代理模型结合遗传算法对流道宽、流道高和岸宽3个几何参数进行了优化设计,以质子交换膜燃料电池的净功率作为优化的目标函数来评价质子交换膜燃料电池的性能.数值模拟应用了商业软件ANSYS FLUENT.优化后的质子交换膜燃料电池流道内具有更高的压力,使更多的反应气体参加电化学反应,因此优化后的质子交换膜燃料电池的性能得到了提高. |
英文摘要: |
A proton exchange membrane fuel cell (PEMFC) is a device that can convert chemical energy stored in fuels into electricity. Three geometry parameters which are channel width, channel height and rib width are optimized applying Kriging surrogate model and genetic algorithm. The net power of the PEMFC is selected as the objective function to evaluate the fuel cell′s performance. The simulation is implemented using the commercial software ANSYS FLUENT. The pressure in the flow channel of the optimized PEMFC is higher, enabling more reactant to participate in the electrochemical reaction, so the performance of the optimized PEMFC is improved. |
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