Current sensorless state of charge estimation approach for onboard battery systems with an unknown current estimator

被引:1
作者
Kim, Wooyong [1 ]
Choi, Kyunghwan [2 ]
机构
[1] Hoseo Univ, Dept Robot, Dangjin 31702, Chungcheongnam, South Korea
[2] Gwangju Inst Sci & Technol, Sch Mech Engn, Gwangju 61005, South Korea
关键词
Battery management system; Disturbance observer; Fault tolerant system; Lithium-ion battery; State of charge estimation; Unknown current estimation; LITHIUM-ION BATTERIES; OPEN-CIRCUIT-VOLTAGE; OF-CHARGE; SERIES; SELECTION; MODELS; CELLS;
D O I
10.1016/j.est.2022.104726
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
Current measurement is essential in a wide variety of lithium-ion battery applications, including electric vehicles and energy storage systems. In onboard battery management systems, regardless of the type of current sensor, it is difficult to ensure the accuracy of the current measurement due to various types of external noise and electrical interference between systems. In extreme cases, a malfunction of the current measurement can occur due to connection loss or sensor fault. Thus, the current measurement is error-prone, which easily decreases the accuracy of the state of charge estimator. This study presents an alternative method to estimate the state of charge of a battery system by estimating the engaged current by using an unknown current estimator instead of relying on erroneous current measurements. There are two main contributions: (1) A nonlinear state space representation of a lithium-ion battery cell is proposed by implicitly transforming the engaged current into internal state variables and equivalent parameters. (2) Based on the disturbance observer for a class of nonlinear systems, the unknown current estimator is established. The effectiveness of the proposed method is verified with a cylindrical battery cell and an experimental investigation with the onboard battery management system.
引用
收藏
页数:10
相关论文
共 50 条
  • [31] Advanced Intelligent approach for state of charge estimation of lithium-ion battery
    Kumar, Deepak
    Rizwan, M.
    Panwar, Amrish K.
    ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS, 2023, 45 (04) : 10661 - 10681
  • [32] A Robust State of Charge Estimation Approach Based on Nonlinear Battery Cell Model for Lithium-Ion Batteries in Electric Vehicles
    Kim, Wooyong
    Lee, Pyeong-Yeon
    Kim, Jonghoon
    Kim, Kyung-Soo
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2021, 70 (06) : 5638 - 5647
  • [33] Real Time State of Charge Estimation of Lithium-Ion Battery Considering Temperature
    Barcellona, Simone
    Codecasa, Lorenzo
    Colnago, Silvia
    D'Amore, Dario
    2024 30TH INTERNATIONAL WORKSHOP ON THERMAL INVESTIGATIONS OF ICS AND SYSTEMS, THERMINIC 2024, 2024,
  • [34] Sliding Mode Observer Design for Battery State of Charge estimation
    Bouchareb, H.
    Saqli, K.
    M'sirdi, N. K.
    Oudghiri Bentaie, M.
    Naamane, A.
    2020 5TH INTERNATIONAL CONFERENCE ON RENEWABLE ENERGIES FOR DEVELOPING COUNTRIES (REDEC), 2020,
  • [35] Battery State-of-Charge Online Estimation Based on H∞ Observer with Current Debasing and Noise Distributions
    Feng D.-W.
    Lu C.
    Chen Y.
    Huang D.-G.
    1600, Univ. of Electronic Science and Technology of China (46): : 547 - 553
  • [36] An adaptive hybrid approach for online battery state of charge estimation
    Lin, Qiongbin
    Hong, Huiyang
    Huang, Ruochen
    Fan, Yuhang
    Chen, Jia
    Wang, Yaxiong
    Dan, Zhimin
    JOURNAL OF ENERGY STORAGE, 2025, 115
  • [37] Estimation of State of Charge, Unknown Nonlinearities, and State of Health of a Lithium-Ion Battery Based on a Comprehensive Unobservable Model
    Gholizadeh, Mehdi
    Salmasi, Farzad R.
    IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2014, 61 (03) : 1335 - 1344
  • [38] Current and voltage control system designs with EKF-based state-of-charge estimator for the purpose of LiFePO4 battery cell charging
    Pavkovic, Danijel
    Premec, Antun
    Krznar, Matija
    Cipek, Mihael
    OPTIMIZATION AND ENGINEERING, 2022, 23 (04) : 2335 - 2363
  • [39] A Novel Current Disturbance Estimation Method for Battery Management Systems in Electric Vehicle
    Xu, Jun
    Li, Shiying
    Cao, Binggang
    8TH INTERNATIONAL CONFERENCE ON APPLIED ENERGY (ICAE2016), 2017, 105 : 2837 - 2842
  • [40] Enhancing the estimation accuracy in low state-of-charge area: A novel onboard battery model through surface state of charge determination
    Ouyang, Minggao
    Liu, Guangming
    Lu, Languang
    Li, Jianqiu
    Han, Xuebing
    JOURNAL OF POWER SOURCES, 2014, 270 : 221 - 237