Novel low-complexity model development for Li-ion cells using online impedance measurement

被引:2
作者
Kulkarni, Abhijit [1 ]
Nadeem, Ahsan [1 ]
Di Fonso, Roberta [1 ]
Zheng, Yusheng [1 ]
Teodorescu, Remus [1 ]
机构
[1] Aalborg Univ, Dept Energy, DK-9220 Aalborg, Denmark
关键词
Li-ion batteries; Battery impedance; Equivalent circuit model; Digital-twin; BATTERY; CHARGE; STATE;
D O I
10.1016/j.est.2024.112029
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
Modeling of Li-ion cells is used in battery management systems (BMS) to determine key states such as state-of- charge (SoC), state-of-health (SoH), etc. Accurate models are also useful in developing a cell-level digital-twin that can be used for protection and diagnostics in the BMS. In this paper, a low-complexity model development is proposed based on the equivalent circuit model (ECM) of the Li-ion cells. The proposed approach uses online impedance measurement at discrete frequencies to derive the ECM that matches closely with the results from the electro-impedance spectroscopy (EIS). The proposed method is suitable to be implemented in a microcontroller with low-computational power, typically used in BMS. Practical design guidelines are proposed to ensure fast and accurate model development. Using the proposed method to enhance the functions of a typical automotive BMS is described. Experimental validation is performed using large prismatic cells and small-capacity cylindrical cells. Root-mean-square error (RMSE) of less than 3% is observed for a wide variation of operating conditions.
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页数:11
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共 37 条
  • [1] Strategies towards a more sustainable aviation: A systematic review
    Afonso, Frederico
    Sohst, Martin
    Diogo, Carlos M. A.
    Rodrigues, Simao S.
    Ferreira, Ana
    Ribeiro, Ines
    Marques, Ricardo
    Rego, Francisco F. C.
    Sohouli, Abdolrasoul
    Portugal-Pereira, Joana
    Policarpo, Hugo
    Soares, Bruno
    Ferreira, Bruna
    Fernandes, Edgar C.
    Lau, Fernando
    Suleman, Afzal
    [J]. PROGRESS IN AEROSPACE SCIENCES, 2023, 137
  • [2] State of charge estimation for lithium-ion batteries based on a novel complex-order model
    Chen, Liping
    Wu, Xiaobo
    Lopes, Antonio M.
    Li, Xin
    Li, Penghua
    Wu, Ranchao
    [J]. COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2023, 125
  • [3] Adaptive state-of-charge estimation of lithium-ion batteries based on square-root unscented Kalman filter
    Chen, Liping
    Wu, Xiaobo
    Lopes, Antonio M.
    Yin, Lisheng
    Li, Penghua
    [J]. ENERGY, 2022, 252
  • [4] A Battery Digital Twin Based on Neural Network for Testing SoC/SoH Algorithms
    Di Fonso, Roberta
    Bharadwaj, Pallavi
    Teodorescu, Remus
    Cecati, Carlo
    [J]. 2022 IEEE 20TH INTERNATIONAL POWER ELECTRONICS AND MOTION CONTROL CONFERENCE, PEMC, 2022, : 655 - 660
  • [5] evlithium, 2024, NMC 50Ah cell from CALB
  • [6] Temperature dependency of diagnostic methods in lithium-ion batteries
    Fly, A.
    Wimarshana, B.
    Bin-Mat-Arishad, I.
    Sarmiento-Carnevali, M.
    [J]. JOURNAL OF ENERGY STORAGE, 2022, 52
  • [7] A review on state of health estimations and remaining useful life prognostics of lithium-ion batteries
    Ge, Ming-Feng
    Liu, Yiben
    Jiang, Xingxing
    Liu, Jie
    [J]. MEASUREMENT, 2021, 174
  • [8] Wideband Measurement Approach for EIS of Lithium-Ion Batteries Using Low-Frequency Concentrated Disturbance
    Geng, Anqi
    Hu, Haitao
    Peng, Yuanzhen
    Zhao, Zhaoyang
    He, Zhengyou
    Gao, Shibin
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2024, 71 (05) : 4851 - 4860
  • [9] Operando electrochemical impedance spectroscopy and its application to commercial Li-ion batteries
    Hallemans, Noel
    Widanage, Widanalage Dhammika
    Zhu, Xinhua
    Moharana, Sanghamitra
    Rashid, Muhammad
    Hubin, Annick
    Lataire, John
    [J]. JOURNAL OF POWER SOURCES, 2022, 547
  • [10] SOC Estimation of Li-ion Batteries With Learning Rate-Optimized Deep Fully Convolutional Network
    Hannan, M. A.
    How, D. N. T.
    Lipu, M. S. Hossain
    Ker, Pin Jern
    Dong, Z. Y.
    Mansur, M.
    Blaabjerg, Frede
    [J]. IEEE TRANSACTIONS ON POWER ELECTRONICS, 2021, 36 (07) : 7349 - 7353