Impedance Characterization and Modeling of Lithium-Ion Batteries Considering the Internal Temperature Gradient

被引:74
作者
Dai, Haifeng [1 ,2 ]
Jiang, Bo [1 ,2 ]
Wei, Xuezhe [1 ,2 ]
机构
[1] Natl Fuel Cell Vehicle & Powertrain Syst Res & En, 4800 Caoan Rd, Shanghai 201804, Peoples R China
[2] Tongji Univ, Sch Automot Studies, 4800 Caoan Rd, Shanghai 201804, Peoples R China
基金
中国国家自然科学基金;
关键词
lithium-ion battery; impedance characterization; temperature gradient; discretization model; CHARGE ESTIMATION; STATE; MANAGEMENT; SPECTROSCOPY;
D O I
10.3390/en11010220
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Battery impedance is essential to the management of lithium-ion batteries for electric vehicles (EVs), and impedance characterization can help to monitor and predict the battery states. Many studies have been undertaken to investigate impedance characterization and the factors that influence impedance. However, few studies regarding the influence of the internal temperature gradient, which is caused by heat generation during operation, have been presented. We have comprehensively studied the influence of the internal temperature gradient on impedance characterization and the modeling of battery impedance, and have proposed a discretization model to capture battery impedance characterization considering the temperature gradient. Several experiments, including experiments with artificial temperature gradients, are designed and implemented to study the influence of the internal temperature gradient on battery impedance. Based on the experimental results, the parameters of the non-linear impedance model are obtained, and the relationship between the parameters and temperature is further established. The experimental results show that the temperature gradient will influence battery impedance and the temperature distribution can be considered to be approximately linear. The verification results indicate that the proposed discretization model has a good performance and can be used to describe the actual characterization of the battery with an internal temperature gradient.
引用
收藏
页数:18
相关论文
共 50 条
  • [41] New method for acquisition of impedance spectra from charge/discharge curves of lithium-ion batteries
    Li, Tao
    Wang, Dingyi
    Wang, Haoran
    JOURNAL OF POWER SOURCES, 2022, 535
  • [42] Adaptive method for sensorless temperature estimation over the lifetime of lithium-ion batteries
    Ludwig, S.
    Zilberman, I
    Oberbauer, A.
    Rogge, M.
    Fischer, M.
    Rehm, M.
    Jossen, A.
    JOURNAL OF POWER SOURCES, 2022, 521
  • [43] Modeling and Observability Study of Lithium-ion Batteries for Automotive Applications
    Zhang, Yun
    Zhang, Chenghui
    2017 CHINESE AUTOMATION CONGRESS (CAC), 2017, : 2418 - 2421
  • [44] Integrating Electrochemical Modeling with Machine Learning for Lithium-Ion Batteries
    Tu, Hao
    Moura, Scott
    Fang, Huazhen
    2021 AMERICAN CONTROL CONFERENCE (ACC), 2021, : 4401 - 4407
  • [45] An Adaptive Peak Power Prediction Method for Power Lithium-Ion Batteries Considering Temperature and Aging Effects
    Ye, Jilei
    Wu, Chao
    Ma, Changlong
    Yuan, Zijie
    Guo, Yilong
    Wang, Ruoyu
    Wu, Yuping
    Sun, Jinlei
    Liu, Lili
    PROCESSES, 2023, 11 (08)
  • [46] Impedance-based capacity estimation for lithium-ion batteries using generative adversarial network
    Kim, Seongyoon
    Choi, Yun Young
    Choi, Jung-Il
    APPLIED ENERGY, 2022, 308
  • [47] A Novel Method for Estimating State of Power of Lithium-Ion Batteries Considering Core Temperature
    Zhang, Ruixue
    Wang, Keyi
    Yu, Zhilong
    Zhao, Gang
    Batteries, 2024, 10 (12)
  • [48] An Intelligent Charging Scheme for Lithium-Ion Batteries of Electric Vehicles Considering Internal Attenuation Modes
    Tian, Jiaqiang
    Yang, Duo
    Zhang, Xu
    Yin, Jianning
    Zhang, Qingping
    IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN POWER ELECTRONICS, 2024, 12 (01) : 82 - 94
  • [49] A novel framework for Lithium-ion battery modeling considering uncertainties of temperature and aging
    Tang, Xiaopeng
    Wang, Yujie
    Zou, Changfu
    Yao, Ke
    Xia, Yongxiao
    Gao, Furong
    ENERGY CONVERSION AND MANAGEMENT, 2019, 180 : 162 - 170
  • [50] Electrochemical characterization tools for lithium-ion batteries
    Ha, Sara
    Pozzato, Gabriele
    Onori, Simona
    JOURNAL OF SOLID STATE ELECTROCHEMISTRY, 2024, 28 (3-4) : 1131 - 1157