基于遗传算法的直接甲醇燃料电池的数学模型及优化设计

Model and Optimum Design of Direct Methanol Fuel Cell Based on Genetic Algorithm

微型直接甲醇燃料电池由于具有系统结构简单、体积小、环境友好、燃料比能量高及便于携带与储存等优点,在便携式电源,如手机、笔记本电脑等上展示出良好的应用前景。研究DMFC的数学模型可以深入了解DMFC中物质的传递过程和电化学机理,为寻找DMFC性能的最优化工作条件提供理论依据。主要依据微型直接甲醇燃料电池中物质传递的基本原理及电化学动力学机理,建立微型直接甲醇燃料电池的一维数学模型,利用遗传算法对其进行优化设计。仿真结果显示当阳极甲醇浓度为2.32mol/L,阴极氧气浓度为0.06mol/L,电流密度为545.67mA/cm2,DMFC的功率密度达到最大值为71.5mW/cm2。

The micro direct methanol fuel cell （DMFC） represents in good propeet of application because of such advantages as simple structure, small size, environmentally safe, high efficiency, easy portable and storage. The mass transfer and electrochemical mechanics of DMFC can be understood by the math model of DMFC, and so the theory foundation can be supplied for the optimization wording conditions of DMFC. This paper establishes one dimension math model of micro DMFC according to the basic participle of mass transfer and electrochemical dynamics. The model is designed optimum using the genetic algorithm. The simulation results indicate that the peak power density of DMFC can reach 71.5 mW/cm^2 on the current density of 5 4 5. 6 7 mA / cm^2 , the methanol concentration of 2.32 mol / L and the oxygen concentration of 0.06 mol/L.