为可再生能源系统设计和开发不同的自适应MPPT控制器:全面分析
Bongani Eswaraiah1, Kethineni Balakrishna2
1Vignan's Foundation for Science Technology and Research, Vadlamudi, India.
Scientific reports
|September 16, 2024
概括
电动汽车 (EV) 使用质子交换膜燃料电池 (PEMFC) 来获得高效的动力. 本研究比较了最大功率点跟踪 (MPPT) 技术,发现适应性步骤值与Cuckoo搜索算法 (ASV与CSA) 对PEMFC系统最有效.
科学领域:
- 电气工程 电气工程
- 可再生能源系统可再生能源系统
- 汽车技术 汽车技术
背景情况:
- 电动汽车 (EV) 由于环境效益和运行成本降低,在全球范围内越来越受欢迎.
- 质子交换膜燃料电池 (PEMFC) 提供快速启动和快速响应,使它们适合电动汽车电源.
- PEMFC 具有非线性电压-电流特性,使得最大功率的提取变得复杂.
研究的目的:
- 调查和比较DC-DC转换器供电PEMFC系统的各种最大功率点跟踪 (MPPT) 技术.
- 评估不同MPPT控制器在优化PEMFC输出功率方面的性能.
主要方法:
- 这项研究检查了六个MPPT控制器:调整的Step Value of Perturb & Observe (ASV与P&O),自适应的步骤大小与增量行为 (ASS与IC),辐射基函数网络 (RBFN),增量步骤模糊逻辑控制器 (IS与FLC),基于持续步骤变化的粒子群优化 (CSV与PSO) 和自适应的步骤值-子搜索算法 (ASV与CSA).
- 性能根据最大功率提取,跟踪速度,沉降时间,输出电压振荡和设计复杂性进行了评估.
主要成果:
- 与Cuckoo搜索算法 (ASV与CSA) 的自适应步骤值与其他评估的MPPT技术相比显示出更高的性能.
- 与CSA配合的ASV在提取最大功率和更快的响应时间方面表现出更高的效率.
结论:
- 在电动汽车应用中,ASV与CSA技术对于最大限度地提高PEMFC的功率输出非常有效.
- 优化的MPPT控制对于燃料电池驱动电动汽车的高效运行至关重要.
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