堆栈(抽象数据类型)
燃料电池
储能
能源管理
能量(信号处理)
计算机科学
国家(计算机科学)
汽车工程
环境科学
工程类
功率(物理)
化学工程
操作系统
算法
数学
量子力学
统计
物理
出处
期刊:Energies
[Multidisciplinary Digital Publishing Institute]
日期:2025-07-22
卷期号:18 (15): 3892-3892
摘要
To address the limitations of conventional single-stack fuel cell hybrid systems using equivalent hydrogen consumption strategies, this study proposes a multi-stack energy management strategy incorporating fuel cell health degradation. Leveraging a fuel cell efficiency decay model and lithium-ion battery cycle life assessment, power distribution is reformulated as an equivalent hydrogen consumption optimization problem with stack degradation constraints. A hybrid Genetic Algorithm–Particle Swarm Optimization (GA-PSO) approach achieves global optimization. The experimental results demonstrate that compared with the Frequency Decoupling (FD) method, the GA-PSO strategy reduces hydrogen consumption by 7.03 g and operational costs by 4.78%; compared with the traditional Particle Swarm Optimization (PSO) algorithm, it reduces hydrogen consumption by 3.61 g per operational cycle and decreases operational costs by 2.66%. This strategy ensures stable operation of the marine power system while providing an economically viable solution for hybrid-powered vessels.
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