Review of Degradation Mechanism and Health Estimation Method of VRLA Battery Used for Standby Power Supply in Power System

Author:

Yu Ruxin1,Liu Gang1,Xu Linbo1,Ma Yanqiang2,Wang Haobin2,Hu Chen3

Affiliation:

1. Zhejiang Zheneng Jiahua Electric Power Generation Co., Ltd., Jiaxing 314201, China

2. Hebei Chuangke Electronic Technology Co., Ltd., Handan 056107, China

3. Laboratory of Operation and Control of Renewable Energy & Storage Systems, China Electric Power Research Institute, Beijing 100192, China

Abstract

As the backup power supply of power plants and substations, valve-regulated lead-acid (VRLA) batteries are the last safety guarantee for the safe and reliable operation of power systems, and the batteries’ status of health (SOH) directly affects the stability and safety of power system equipment. In recent years, serious safety accidents have often occurred due to aging and failure of VRLA batteries, so it is urgent to accurately evaluate the health status of batteries. Accurate estimation of battery SOH is conducive to real-time monitoring of single-battery health information, providing a reliable guarantee for fault diagnosis and improving the overall life and economic performance of the battery pack. In this paper, first, the floating charging operation characteristics and aging failure mechanism of a VRLA battery are summarized. Then, the definition and estimation methods of battery SOH are reviewed, including an experimental method, model method, data-driven method and fusion method. The advantages and disadvantages of various methods and their application conditions are analyzed. Finally, for a future big data power system backup power application scenario, the existing problems and development prospects of battery health state estimation are summarized and prospected.

Funder

Zhejiang Zheneng Jiahua Electric Power Generation Co., Ltd.

Publisher

MDPI AG

Subject

Materials Chemistry,Surfaces, Coatings and Films,Surfaces and Interfaces

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Electric bikes charging anomaly detection from alternating current side based on big data;Engineering Applications of Artificial Intelligence;2024-10

2. Investigation of Change in EIS of Lead-acid Battery During the Water Loss;2024 9th Asia Conference on Power and Electrical Engineering (ACPEE);2024-04-11

3. Battery applications;Nanostructured Materials Engineering and Characterization for Battery Applications;2024

4. Bidirectional Long Short-Term Memory Model of SoH Prediction for Gelled-Electrolyte Batteries under Charging Conditions;Gels;2023-12-17

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3