储能科学与技术 ›› 2019, Vol. 8 ›› Issue (5): 807-812.doi: 10.12028/j.issn.2095-4239.2019.0041

• 进展与评述 • 上一篇    下一篇

退役锂离子电池健康状态评估方法综述

李金东, 古月圆, 王路阳, 吴旭   

  1. 华中科技大学环境科学与工程学院, 湖北 武汉 430074
  • 收稿日期:2019-03-25 修回日期:2019-04-01 出版日期:2019-09-01 发布日期:2019-04-11
  • 通讯作者: 吴旭,教授,研究方向为环境电化学工程,E-mail:profxuwu@hust.edu.cn。
  • 作者简介:李金东(1996-),男,硕士研究生,研究方向为锂离子电池健康状态评估,E-mail:lijindong@hust.edu.cn
  • 基金资助:
    国家自然科学基金青年基金(51704122)。

Review on state of health estimation of retired lithium-ion batteries

LI Jindong, GU Yueyuan, WANG Luyang, WU Xu   

  1. School of Environmental Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
  • Received:2019-03-25 Revised:2019-04-01 Online:2019-09-01 Published:2019-04-11

摘要: 由于电池组中电池单体之间存在性能差异,退役锂离子电池在投入梯次利用前需要借助健康状态(SOH)评估技术进行电池单体的分类与配组。健康状态评估系统的构建涉及电池建模、电池测试、数据处理、算法开发等各种技术问题。目前通过基于模型的参数识别与直接提取健康因子是构建SOH评估体系的两种主要思路。在电池模型的简化、测试工况的设计、健康因子的选择和算法的应用与优化等方面已经有了很多研究。如何在缩短电池测试时间的同时提高评估系统的泛化能力是目前该研究领域的主要问题,这些问题的解决对于SOH评估系统真正在梯次利用锂离子电池的产业化中发挥作用至关重要。在未来的研究中通过优化测试工况和数据融合等技术,有望开发出性能更好的SOH评估系统。

关键词: 锂离子电池, 梯次利用, 健康状态评估

Abstract: Due to the discrepancy among the batteries in the retired battery pack, to implement the classification and matching for batteries through state of health (SOH) estimating technology is a key problem of the industrialization of second use of retired Li-ion batteries. The construction of a SOH estimation system for retired Li-ion batteries involves various technical issues such as battery modelling, battery testing, data processing and algorithm development. Identification of model parameters and health indicators extraction are two main technical routes for SOH system construction. There are many researchers have studied in the battery model simplification, battery test method design, health indicators selection and algorithm optimization. The analysis of the research progress indicates that the major problems of the SOH estimating system are long test time and low generalization ability. The SOH estimation system with better performances would be developed by test method optimization and data fusion technology.

Key words: lithium-ion batteries, second use, state of health estimation

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