• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2021, Vol. 57 ›› Issue (14): 105-117.doi: 10.3901/JME.2021.14.105

• 特邀专栏:电源系统设计、管理与大数据 • 上一篇    下一篇



王学远1,2, 李日康2,3, 魏学哲2,3, 戴海峰2,3, 郑岳久4   

  1. 1. 同济大学电子与信息工程学院 上海 201804;
    2. 同济大学新能源汽车工程中心 上海 201804;
    3. 同济大学汽车学院 上海 201804;
    4. 上海理工大学机械工程学院 上海 200093
  • 收稿日期:2020-07-08 修回日期:2021-01-14 出版日期:2021-09-15 发布日期:2021-09-15
  • 通讯作者: 戴海峰(通信作者),男,1981年出生,博士,教授,博士研究生导师。主要研究方向为蓄电池管理技术。E-mail:tongjidai@tongji.edu.cn
  • 作者简介:王学远,男,1990年出生,博士后。主要研究方向为锂离子电池阻抗建模、测量与应用。E-mail:7wangxueyuan@tongji.edu.cn
  • 基金资助:

Study on Remaining Useful Life Prediction of Lithium-ion Batteries Based on Charge Transfer Resistance

WANG Xueyuan1,2, LI Rikang2,3, WEI Xuezhe2,3, DAI Haifeng2,3, ZHENG Yuejiu4   

  1. 1. College of Electronic and Information Engineering, Tongji University, Shanghai 201804;
    2. Clean Energy Automotive Engineering Center, Tongji University, Shanghai 201804;
    3. School of Automotive Studies, Tongji University, Shanghai 201804;
    4. College of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093
  • Received:2020-07-08 Revised:2021-01-14 Online:2021-09-15 Published:2021-09-15

摘要: 锂离子电池的剩余寿命预测对实现高效、精准的电池管理和维护具有重要意义。电化学阻抗能够反映锂离子电池内部物理化学过程特性,在电池寿命问题研究中被广泛应用。特别地,传荷电阻描述电极界面过程进行的难易程度,可用来表征电池的寿命状态。通过开展四种工况的锂离子电池老化试验,获取传荷电阻随寿命衰减的演变规律。采用贝叶斯信息准则,对多种寿命衰减经验模型进行评价,选择并确立一阶多项式形式的经验模型。在此基础上,提出基于粒子滤波算法的剩余寿命预测方法。结果表明该方法可准确实现锂离子电池的剩余寿命预测,从而能够为电池管理和维护提供必要的电池寿命信息。

关键词: 锂离子电池, 阻抗, 传荷电阻, 粒子滤波算法, 剩余寿命

Abstract: Prediction of remaining useful life facilitates the efficient and appropriate management and assessment for lithium-ion batteries. Electrochemical impedance can reflect properties of physical and chemical processes inside a lithium-ion battery. It is widely used in studies of battery life issues. Especially, the charge transfer resistance describes the difficulty of the reaction at the interphase of the electrodes. It can be applied to characterize the aging state. Through the experiments under four aging conditions, the evolution of the charge transfer resistance with the aging process is obtained. Several empirical aging models are evaluated with the Bayesian information criterion. And a first-order polynomial aging model is chosen and established. On this basis, a remaining useful life prediction method based on the particle filter algorithm is proposed. The results show that the remaining useful life of the lithium-ion batteries can be accurately predicted with the method, thus providing the necessary battery life information for the battery management and assessment.

Key words: lithium-ion batteries, impedance, charge transfer resistance, particle filter algorithm, remaining useful life