一个模糊预测电流控制与实时硬件为PEM燃料电池系统的PEM燃料电池系统
Badreddine Kanouni1, Abd Essalam Badoud2, Saad Mekhilef3
1Setif Automatic Laboratory, Electrical Engineering Department, Ferhat Abbas University, Setif 1, Setif, Algeria.
Scientific reports
|November 7, 2024
概括
本研究介绍了一种智能模糊逻辑预测电流控制 (FC-PCC) 算法,用于在质子交换膜燃料电池系统中增强最大功率点跟踪 (MPPT). 这种新的方法实现了更快,更精确的功率提取,同时确保了稳定的运行.
科学领域:
- 可再生能源系统可再生能源系统
- 电力电子 电力电子 电力电子
- 控制系统 控制系统
背景情况:
- 质子交换膜燃料电池 (PEMFC) 需要高效的最大功率点跟踪 (MPPT) 才能产生最佳的能量.
- 传统的MPPT方法如Perturb and Observe (P&O) 和Incremental Conductance (IC) 在跟踪速度和精度方面面临挑战,特别是在不同的环境条件下.
- 三级增压转换器 (TLBC) 在PEMFC系统中使用,但需要有效的电压平衡策略.
研究的目的:
- 开发和评估用于PEMFC系统中MPPT的智能模糊逻辑预测电流控制 (FC-PCC) 算法.
- 为了提高TLBCs的MPPT控制器的跟踪速度,精度和电压平衡能力.
- 在动态条件下,对拟议的FC-PCC算法的性能与传统的MPPT技术进行评估.
主要方法:
- 模糊逻辑控制器与MPPT的预测电流控制策略的集成.
- 利用PEMFC数据来确定最大功率点 (MPP) 和参考电流.
- 使用硬件在循环系统与PLECS RT Box 1实时模拟器实现和测试.
主要成果:
- FC-PCC算法证明了最大功率点 (MPP) 的快速跟踪.
- 在三级增压转换器内实现了电容器电压的精确平衡.
- 拟议的方法优于P&O和IC方法,显示追踪时间减少15%,与MPP偏差5%,在环境变化下具有优越的稳定性.
结论:
- FC-PCC算法为PEMFC系统中的MPPT提供了一个计算高效和有效的解决方案.
- 与传统方法相比,智能控制策略显著提高了跟踪性能和电压稳定性.
- 这种方法提供了一种强大可靠的MPPT技术,适合各种PEMFC应用和操作条件.
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