PEMFC流道的多目标优化

Multi-objective optimization of PEMFC flow channel

流道是质子交换膜燃料电池(PEMFC)的重要组成部分,能够通过影响PEMFC的传质表现影响其性能。建立了一个单直流道的三维单相非等温PEMFC数值模型,以此为基础,采用基于非支配排序的多目标遗传算法(NSGA-II)以PEMFC的总功率和寄生功耗为目标对流道结构进行优化。在优化后得到的Pareto前沿中选择最优的流道结构。结果表明,相比于初始的矩形流道,最优流道的横截面为梯形截面,而且整个流道沿轴向呈现锥形结构。在0.5V电压下,最优流道下的PEMFC总功率较优化前提高了10.21%,寄生功耗降低了0.032%。不仅如此,优化后的PEMFC具有更均匀的氧气和电流密度分布。

Flow channel is an important part of proton exchange membrane fuel cell(PEMFC),which can affect the performance of PEMFC by varying the mass transfer performance in the flow channel.A three-dimensional single-phase non-isothermal PEMFC numerical model forstraight channel is established.The total power and parasitic power consumption is taken as optimization goal,a non-dominated sorting based multi-objective genetic algorithm(NSGA-II)is used to optimize the flow channel structure.The optimal flow channel structure is selected from the Pareto front obtained after optimization.The results show that,compared with original rectangular flow channel,the trapezoidal cross section is optimal selection,with a tapered gradient along axial direction.Under 0.5 V voltage,the total power of PEMFC with the optimal flow channel is increased by 10.21%compared to that not optimized,and the parasitic power consumption is reduced by 0.032%.Moreover,the optimized PEMFC has a more uniform distribution of oxygen and current density.