In this paper, the problem concerned is to find the optimum values of the seven uncertain parameters ξ1, ξ2, ξ3, ξ4, λ, Rc, and β of the semi-empirical equation that defines the proton exchange membrane fuel cell (PEMFC) polarization (I/V) relationship using a recent optimization technique, the marine predator algorithm (MPA). The main target of this study is to obtain a very precise PEMFC steady state model. The MPA mimics the different random movements of marine predators when foraging and is believed to always converge to a stable value. Three popular stacks namely the Ballard Mark 5 kW, BCS stack 500 W, and Temasek 1 kW are investigated and efficiently modeled. Numerical results show the high accuracy of the MPA-based model when compared with other recently published optimization techniques.

本文所关注的问题是寻找七个不确定参数 ξ1、ξ2、ξ3、ξ4、λ、Rc和β的最优值使用最近的优化技术海洋捕食者算法 (MPA) 定义质子交换膜燃料电池 (PEMFC) 极化 (I/V) 关系的半经验方程。本研究的主要目标是获得一个非常精确的 PEMFC 稳态模型。MPA 在觅食时模仿海洋捕食者的不同随机运动，并且被认为总是收敛到一个稳定值。三种流行的电池组，即 Ballard Mark 5 kW、BCS 电池组 500 W 和 Temasek 1 kW 进行了研究和有效建模。与最近发布的其他优化技术相比，数值结果表明基于 MPA 的模型具有较高的准确性。