发电技术 ›› 2021, Vol. 42 ›› Issue (5): 537-546.DOI: 10.12096/j.2096-4528.pgt.21074

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锂离子电池荷电状态与健康状态估计方法

李沂洹1(), 李慷1,*(), 余渐2   

  1. 1 利兹大学电子电气工程学院, 英国 利兹LS2 9JT
    2 苏格兰电力公司, 英国 格拉斯哥G2 5AD
  • 收稿日期:2021-06-07 出版日期:2021-10-31 发布日期:2021-10-13
  • 通讯作者: 李慷
  • 作者简介:李沂洹(1992), 女, 博士研究生, 研究方向为电池管理、状态估计等, elyli2@leeds.ac.uk
  • 基金资助:
    英国工程与自然科学研究理事会项目(EP/R030243/1)

Estimation Approaches for States of Charge and Health of Lithium-ion Battery

Yihuan LI1(), Kang LI1,*(), James YU2   

  1. 1 School of Electrical and Electronic Engineering, University of Leeds, Leeds LS2 9JT, UK
    2 SP Energy Networks, Glasgow G2 5AD, UK
  • Received:2021-06-07 Published:2021-10-31 Online:2021-10-13
  • Contact: Kang LI
  • Supported by:
    Engineering and Physical Sciences Research Council(EP/R030243/1)

摘要:

电池储能系统是实现碳中和最重要、最有效的手段之一,其大规模应用对电池运行过程中的安全性提出了更高的要求。实时准确的电池状态估计为保障电池的安全稳定运行提供重要信息,是电池管理系统(battery management system,BMS)的一项重要功能。然而,由于复杂的操作条件和电池内部的电化学反应,很难准确地评估电池的内部状态。针对电池荷电状态(state of charge,SOC)和健康状态(state of health,SOH)这2个电池系统中的重要参数,系统回顾了当前常用的SOC和SOH估计方法,总结了各种方法的特点及其在实际应用中所面临的主要挑战,并在此基础上对电池SOC和SOH估计技术未来的发展提出展望,为电池状态估计技术的进一步研究提供参考依据。

关键词: 锂离子电池, 储能, 状态估计, 电池管理系统(BMS)

Abstract:

Battery energy storage system is one of the most important and effective means to achieve carbon neutrality, its large-scale applications put forward higher requirements for the battery operating safety. Accurate and real-time battery state estimation is an important function of battery management systems, and it provides critical information for ensuring safe and reliable operation of batteries. However, it is not an easy task to accurately estimate the battery internal state due to the complex operating conditions and the complicated electrochemical reactions inside the battery. This paper provided a systematic review of the state-of-the-art techniques on the state of charge (SOC) and state of health (SOH) estimation of batteries. The advantages and main challenges existing in practical applications of different techniques were analyzed and compared. Then, the future development needs for battery SOC and SOH estimation techniques were prospected, which provides references for further research in battery state estimation

Key words: lithium-ion battery, energy storage, state estimation, battery management system (BMS)

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