Wang Zheng, Rezaie Mehrdad, Fathi Gholamreza
Chongqing Chemical Industry Vocational College, Chongqing, 401220, China.
Department of Electrical Engineering, Malayer University, Malayer, Iran.
Sci Rep. 2025 May 14;15(1):16682. doi: 10.1038/s41598-025-01637-4.
This research introduces a novel optimal control strategy for Proton Exchange Membrane Fuel Cells (PEMFCs) utilizing a DC/DC converter, aimed at enhancing performance and longevity. The core of this strategy is an Improved Coot Optimizer algorithm (ICOA), designed to optimize a PID controller for precise voltage regulation of the PEMFC stack. The ICOA incorporates self-adaptive and chaotic mechanisms to improve solution quality and prevent premature convergence. Simulation results demonstrate that the proposed ICOA-optimized PID controller significantly reduces voltage ripples and overshoot, key factors in improving PEMFC lifetime. Specifically, compared to non-optimized performance with a 2.47% overshoot and 4.7 s settling time, the ICOA-optimized system exhibits superior dynamic response and stability. Comparative analyses against three other control techniques confirm a wide system enhancement, evidenced by a substantial reduction in both current and overshoot ripples. Algorithm verification using benchmark functions shows the ICOA achieves lower mean values and standard deviations, with p-values indicating statistically significant improvements (p < 0.05) in Root Mean Square Error (RMSE) compared to COA, MVO, EPO, and LOA algorithms, validating its enhanced optimization capabilities for PEMFC control.
本研究介绍了一种利用DC/DC转换器的质子交换膜燃料电池（PEMFC）新型最优控制策略，旨在提高性能和延长使用寿命。该策略的核心是一种改进的黑鸭优化算法（ICOA），旨在优化PID控制器，以精确调节PEMFC电池堆的电压。ICOA纳入了自适应和混沌机制，以提高解的质量并防止过早收敛。仿真结果表明，所提出的ICOA优化PID控制器显著降低了电压纹波和超调量，这是提高PEMFC寿命的关键因素。具体而言，与具有2.47%超调量和4.7秒稳定时间的未优化性能相比，ICOA优化系统表现出卓越的动态响应和稳定性。与其他三种控制技术的对比分析证实了系统有广泛的提升，电流纹波和超调量均大幅降低就是证明。使用基准函数进行的算法验证表明，ICOA实现了更低的均值和标准差，p值表明与黑鸭算法（COA）、蛾火优化算法（MVO）、帝王蝶优化算法（EPO）和狮子优化算法（LOA）相比，均方根误差（RMSE）有统计学上的显著改善（p < 0.05），验证了其在PEMFC控制方面增强的优化能力。
