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基于燃料电池/电池/超级电容的交通电气化系统混合供电大信号稳定性分析与改进策略
Large-Signal Stability Analysis and Improvement Strategy for Fuel Cell/Battery/Supercapacitor-Based Hybrid Power Supply System of Transportation Electrification Systems
| 作者 | Wenjie Ao · Jiawei Chen · Jie Chen · Pengwei Chen |
| 期刊 | IEEE Journal of Emerging and Selected Topics in Power Electronics |
| 出版日期 | 2024年12月 |
| 技术分类 | 储能系统技术 |
| 技术标签 | 储能系统 下垂控制 |
| 相关度评分 | ★★★★★ 5.0 / 5.0 |
| 关键词 | 混合供电系统 大信号稳定性分析 极端负载切换 有源电容 区域吸引估计 |
语言:
中文摘要
融合多种电源动态特性的混合供电系统(HPSS)在交通电气化中具有广阔应用前景。然而,负载大幅突变或高脉冲功率等极端工况易引发电力系统失稳,超出小信号分析适用范围。本文基于吸引域估计(ROA),对虚拟阻抗下垂参数及PI调节器在极端负载切换下的大信号稳定性进行综合分析,阐明系统参数与负载功率对稳定性的影晌。通过引入主动电容吸收脉冲功率,显著提升系统稳定性。实验结果验证了所提分析方法的有效性与结论的正确性。
English Abstract
Hybrid power supply systems (HPSSs), which integrate the dynamic properties of different power sources, are a promising solution for transportation electrification systems. However, extreme cases such as large variations of load like large step-changing load and high peak-to-average ratio pulsed power load are highly susceptible to power supply system destabilization, which is beyond the scope of small-signal analysis. In this article, a comprehensive large-signal stability analysis for HPSSs considering variation in virtual impedance droop parameters and proportional and integral (PI) regulators under extreme load switching conditions is conducted based on the region of attraction estimation (ROA). On this basis, the impact of system parameters and load power on the large-signal stability is elaborated. The stability of the system is greatly improved by the adoption of active capacitors to absorb the pulsed power. The effectiveness of the proposed large-signal stability analysis method and the correctness of the analyzing results are verified through experiment results.
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SunView 深度解读
该混合供电系统大信号稳定性分析技术对阳光电源储能与交通电气化产品具有重要应用价值。研究中的虚拟阻抗下垂控制与吸引域估计方法可直接应用于ST系列储能变流器的多源协调控制,优化燃料电池-储能混合系统在极端负载突变下的稳定性。主动电容吸收脉冲功率的策略对车载OBC充电机和充电桩产品的大功率脉冲工况适应性提升具有指导意义。所提PI参数与下垂系数的大信号稳定域分析方法可完善PowerTitan储能系统的参数设计流程,增强系统在电网扰动和负载冲击下的鲁棒性,为构网型GFM控制策略在交通电气化场景的工程化应用提供理论支撑。