全钒液流电池建模及SOC在线估计研究进展

doi:10.19799/j.cnki.2095-4239.2023.0734

储能科学与技术 ›› 2024, Vol. 13 ›› Issue (3): 1036-1049.doi: 10.19799/j.cnki.2095-4239.2023.0734

全钒液流电池建模及SOC在线估计研究进展

张爱芳¹(), 魏邦达², 李卓昊², 杨洋¹, 杨添强², 姚俊¹, 张杰¹, 刘飞¹, 李浩秒²(), 王康丽², 蒋凯²

^1.国网电力科学研究院武汉南瑞有限责任公司
^2.华中科技大学强电磁技术全国重点实验室，湖北武汉 430074

收稿日期:2023-10-17 修回日期:2023-11-01 出版日期:2024-03-28 发布日期:2024-03-28
通讯作者: 李浩秒 E-mail:128196188@qq.com;lihm@hust.edu.cn
作者简介:张爱芳（1977—），女，硕士，正高级经济师，研究方向为综合能源及储能，E-mail：128196188@qq.com；
基金资助:
国网电力科学研究院武汉南瑞有限责任公司自筹科技项目(524625220010)

Research progress on modeling and SOC online estimation of vanadium redox-flow batteries

Aifang ZHANG¹(), Bangda WEI², Zhuohao LI², Yang YANG¹, Tianqiang YANG², Jun YAO¹, Jie ZHANG¹, Fei LIU¹, Haomiao LI²(), Kangli WANG², Kai JIANG²

^1.Wuhan Nari Limited Liability Company of State Grid Electric Power Research Institute
^2.State Key Laboratory of Advanced Electromagnetic Technology, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China

Received:2023-10-17 Revised:2023-11-01 Online:2024-03-28 Published:2024-03-28
Contact: Haomiao LI E-mail:128196188@qq.com;lihm@hust.edu.cn

摘要/Abstract

摘要：

全钒液流电池（VRFB）具有高安全、长寿命的优势，在大规模电力储能领域中具有广阔的应用前景。高精度的电池模型及准确的电池荷电状态（SOC）估计是全钒液流电池实际应用的重要技术基础，也是其规模应用面临的主要挑战。本文对全钒液流电池仿真模型、模型参数辨识、SOC监测与在线估计，以及全钒液流电池特有的SOC估计影响因素进行综述。首先介绍了电化学模型和等效电路模型2类仿真模型，分析比较了几种用于VRFB的等效电路模型的原理及优缺点。重点综述了全钒液流电池荷电状态监测方法，包括：安时积分法、开路电压法、电位滴定法、电导率法和光学分析法，以及更具工程应用前景的荷电状态在线估计方法。总结了全钒液流电池模型参数离线与在线辨识技术，介绍了基于滤波算法与数据驱动算法的荷电状态在线估计方法。在全钒液流电池SOC估计特异性影响因素方面，讨论了包括钒离子的跨膜迁移、负极氧化副反应、负极析氢反应和温度对参数辨识与荷电状态估计的影响规律，总结展望了全钒液流电池建模及SOC在线估计面临的问题及未来研究方向。

关键词: 全钒液流电池, 仿真模型, 模型参数辨识, 荷电状态, 在线估算

Abstract:

The vanadium redox-flow battery (VRFB) offers the advantages of high security and long life, and has broad application prospects in the field of large-scale energy storage. High-precision battery models and accurate battery state-of-charge (SOC) estimation are important technical foundations for the practical application of VRFBs, and the main challenge that must be overcome for their large-scale application. This paper reviews the simulation model of VRFBs, the identification of model parameters, SOC monitoring with online estimation, and the factors specific to VRFB that affect SOC estimation. Two types of simulation models, an electrochemical model and an equivalent-circuit model, are introduced.The principles, advantages, and disadvantages of several equivalent-circuit models for VRFBs are analyzed and compared. This paper focuses on methods to monitor the SOC of VRFBs, including the ampere-time integration method, open-circuit voltage method, potential titration method, conductivity method, optical analysis method, and SOC online estimation method that are promising for engineering applications. The paper summarizes the techniques of offline and online identification of the model parameters of VRFBs and introduces the SOC online estimation method, which is based on the filtering and data-driven algorithms. To understand the specific factors that affect SOC estimation of VRFB, we focus on the transmembrane migration of vanadium ions, the negative electrode oxidation side reaction, the negative electrode hydrogen precipitation reaction, and temperature on parameter identification and SOC estimation. Finally, this paper summarizes the outlook for this technology and proposes possible research directions for modeling and SOC online estimation of VRFBs.

Key words: vanadium redox-flow battery, simulation model, model parameter identification, state of charge, online estimation

中图分类号:

TM 911

张爱芳, 魏邦达, 李卓昊, 杨洋, 杨添强, 姚俊, 张杰, 刘飞, 李浩秒, 王康丽, 蒋凯. 全钒液流电池建模及SOC在线估计研究进展[J]. 储能科学与技术, 2024, 13(3): 1036-1049.

Aifang ZHANG, Bangda WEI, Zhuohao LI, Yang YANG, Tianqiang YANG, Jun YAO, Jie ZHANG, Fei LIU, Haomiao LI, Kangli WANG, Kai JIANG. Research progress on modeling and SOC online estimation of vanadium redox-flow batteries[J]. Energy Storage Science and Technology, 2024, 13(3): 1036-1049.

图/表 7

图1

表1

VRFB等效电路模型对比"

模型	建模时重点关注问题	优缺点及应用场景
Thevenin模型	考虑了极化效应， $R 1$ 和 $C 1$ 环节用以描述电池内部的极化现象，可以在一定程度上模拟瞬态响应^[42]	模型简单，参数较少，易于做参数辨识；无法进行更精确的分析^[45]
PNGV模型	考虑了电池的动态响应过程、极化效应和电流累积效应	模型结构较为简单；比较适用于分析电池工作时电流、电压变化的情形，不适用于电池稳定充放电的情形^[44]
交流阻抗模型	根据电池的交流阻抗谱进行建模分析^[43]	模型较为简单，易于搭建，能有效反映VRFB的充放电特性^[45]
等效损耗模型	考虑了VRFB充放电过程中产生的各种损耗和系统的瞬态响应	结构简单、计算方便、仿真速度快，重点关注了VRFB的充放电特性^[46]
基于电化学机理的改进等效电路模型	考虑了浓差极化、电化学极化和泵损对输出端电压的影响^[47]	模型较为复杂，参数较多，不易进行参数辨识^[47]，需要进行简化处理
电热耦合模型	考虑了电化学行为和热行为之间的耦合效应，使用三阶考尔网络对VRFB系统中的传热过程进行建模，充分考虑了热效应	模型复杂，参数较多，耦合了电路模型和热力学模型，不便于进行建模和参数辨识^[48]
分数阶模型	VRFB被模拟为一个欧姆内阻和两个串联的半电池，考虑了VRFB的阻抗变化	模型较为复杂，不便于参数辨识，但可用于研究VRFB在可变充放电功率情况下的动态响应^[49]

表1

图2

图3

图4

图5

表2

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SOC统计方法	优点	缺点
EKF	计算效率高，应用广泛，适应测量噪声和过程噪声	线性化误差大，对初值敏感，不适用于高维空间

UKF	无需手动线性化，避免协方差不正定，鲁棒性强	不适用于高维空间，需要调节参数，易发散

SR-UKF	避免协方差不正定，数值稳定性好	计算复杂，需要调节参数，适用范围小

AEKF	适应性强，鲁棒性强，线性误差小	需要调节参数，对初值敏感，适用范围小

SRCQKF	避免协方差不正定，更稳定，线性误差小	计算复杂，适用范围小

STEKF	可调整协方差矩阵，跟踪性能强，数值稳定性好	计算复杂，适用范围小

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全钒液流电池建模及SOC在线估计研究进展

Research progress on modeling and SOC online estimation of vanadium redox-flow batteries

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