磷酸铁锂储能电站主动在线多源监测和分级预警系统

doi:10.16265/j.cnki.issn1003-3033.2025.07.0708

中国安全科学学报 ›› 2025, Vol. 35 ›› Issue (7): 184-191.doi: 10.16265/j.cnki.issn1003-3033.2025.07.0708

磷酸铁锂储能电站主动在线多源监测和分级预警系统

许晴晴¹(), 陈杰¹^,^**(), 高保彬¹, 王燕¹, 王健¹, 程祖田²

¹ 河南理工大学安全科学与工程学院, 河南焦作 454003
² 中国电建集团河南省电力勘测设计院有限公司, 河南郑州 451450

收稿日期:2025-03-24 修回日期:2025-05-16 出版日期:2025-07-28
通信作者:
** 陈杰(1993—),男,河南安阳人,博士,讲师,硕士生导师,主要从事锂离子电池安全方面的研究。E-mail:chenj1996@hpu.edu.cn。
作者简介:

许晴晴 (2000—),女,河南焦作人,硕士研究生,主要研究方向为电化学储能电站的安全理论与技术。E-mail:13782830668@163.com。
高保彬教授
王燕教授
王健副教授
程祖田高级工程师
基金资助:
河南省科技攻关项目(242102321108); 中国工程科技发展战略河南研究院咨询研究项目(2024HENZDB05); 河南省重点研发专项项目(241111322400)

Active online multi-source monitoring and hierarchical early warning system for LiFePO₄ energy storage power station

XU Qingqing¹(), CHEN Jie¹^,^**(), GAO Baobin¹, WANG Yan¹, WANG Jian¹, CHENG Zutian²

¹ School of Safety Science and Engineering, Henan Polytechnic University, Jiaozuo Henan 454003, China
² Henan Electric Power Survey & Design Institute, POWERCHINA, Zhengzhou Henan 451450, China

Received:2025-03-24 Revised:2025-05-16 Published:2025-07-28

摘要/Abstract

摘要： 为提升锂离子电池储能电站事故监测效果和预警效率,降低火灾发生概率,针对预制舱式磷酸铁锂(LFP)电池储能电站存在的被动监测延时、单一参量监测不准确以及灾变风险分级模糊等问题,设计一套 LFP 储能电站主动在线多源监测与分级预警系统。首先,分析储能电站热失控及火灾发生过程,基于不同层级构建特征指标集,包括内部温度(单体)、内压-声音(电池包)、H₂和CO浓度(电池簇)、烟雾特征图像(电池舱),并规划详细的监测实施路径;然后,根据4个层级对应的4级预警,制定预警策略,明确预警流程。结果表明:该监测预警系统在LFP储能电站热失控极早期预警方面有显著优势,尤其是在2C过充条件下,可提前38.9 min预警32 Ah电池单体的热失控;在0.5C过充条件下提前53.2 min预警344 Ah电池模组的燃烧。

关键词: 磷酸铁锂(LFP)电池, 储能电站, 多源监测, 分级预警, 热失控, 火灾

Abstract:

In order to enhance the accident monitoring effect and early warning efficiency of lithium-ion battery energy storage power stations and reduce the probability of fire occurrence, aiming at the problems existing in prefabricated cabin LiFePO₄ (LFP) battery energy storage power stations, such as passive monitoring delay, inaccurate monitoring of a single parameter, and ambiguous classification of disaster risks, an active online multi-source monitoring and hierarchical early warning system for LFP energy storage power stations was designed. Firstly, the thermal runaway and fire occurrence process of the energy storage power station was analyzed. The characteristic index set of each level was constructed, which is specific: internal temperature (single), internal pressure-sound (battery Pack), H₂ and CO concentration (battery cluster), smoke characteristic image (battery chamber), and plan a detailed monitoring implementation path. Then, based on the four-level early warning corresponding to the four levels, formulate the early warning strategy and clarify the early warning process. Experimental results demonstrated that: This monitoring and early warning system can effectively achieve the early warning of LFP energy storage power stations. Under 2C overcharging conditions, it can give an early warning of the thermal runaway of 32 Ah battery cells 38.9 min in advance. The combustion of the 344 Ah battery module was warned 53.2 min in advance under the condition of 0.5C overcharging. This study proves that this system can provide an effective guarantee for the safe operation of energy storage power stations.

Key words: LiFePO₄ (LFP) battery, energy storage power station, multi-source monitoring, hierarchical early warning, thermal runaway, fire

中图分类号:

X924.4安全控制技术

许晴晴, 陈杰, 高保彬, 王燕, 王健, 程祖田. 磷酸铁锂储能电站主动在线多源监测和分级预警系统[J]. 中国安全科学学报, 2025, 35(7): 184-191.

XU Qingqing, CHEN Jie, GAO Baobin, WANG Yan, WANG Jian, CHENG Zutian. Active online multi-source monitoring and hierarchical early warning system for LiFePO₄ energy storage power station[J]. China Safety Science Journal, 2025, 35(7): 184-191.

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参考文献 19

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通信方式	特点	适用场景
CAN	可靠性高、实时性强、抗干扰能力强	适用于复杂环境下的短距离通信,如BMS相关组件与电池簇内传感器的连接
LAN	传输速率较高、带宽较大,能迅速完成大量数据的传输与交互	适用于需要进行大规模数据流转的应用场景,例如BMS与EMS之间的数据交互
RS485	接口简单、成本较低,并且可以实现较长距离的通信	适用于长距离且对速率要求不高的稳定通信场景,例如与人机交互相关的连接

特征事件	预警级别	比起火提前时间/min
过充开始	—	—
电池内部温度超50 ℃ 且持续3 s温升速率 ≥0.2 ℃/s	一级	53.2
电池包爆破阀开启	二级	13.2
H₂被探测到	三级	12.9
CO被探测到	三级	12.6
冒烟	四级	2.2
起火	四级	0

磷酸铁锂储能电站主动在线多源监测和分级预警系统

Active online multi-source monitoring and hierarchical early warning system for LiFePO₄ energy storage power station

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磷酸铁锂储能电站主动在线多源监测和分级预警系统

Active online multi-source monitoring and hierarchical early warning system for LiFePO4 energy storage power station

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Active online multi-source monitoring and hierarchical early warning system for LiFePO₄ energy storage power station