Combined State of Charge and State of Health estimation over lithium-ion battery cell cycle lifespan for electric vehicles

被引:512
|
作者
Zou, Yuan [1 ]
Hu, Xiaosong [2 ]
Ma, Hongmin [1 ]
Li, Shengbo Eben [3 ]
机构
[1] Beijing Inst Technol, Sch Mech Engn, Natl Engn Lab Elect Vehicles, Beijing 100081, Peoples R China
[2] Univ Calif Berkeley, Energy Controls & Applicat Lab, Berkeley, CA 94720 USA
[3] Tsinghua Univ, Dept Automot Engn, State Key Lab Automot Safety & Energy, Beijing 100084, Peoples R China
基金
中国国家自然科学基金;
关键词
Electric vehicles; Lithium-ion battery; Kalman filter; Recursive least squares; State of charge; State of health; OF-CHARGE; MANAGEMENT-SYSTEMS; CAPACITY FADE; PART; MODEL; PACKS; PARAMETER;
D O I
10.1016/j.jpowsour.2014.09.146
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
A combined SOC (State Of Charge) and SOH (State Of Health) estimation method over the lifespan of a lithium-ion battery is proposed. First, the SOC dependency of the nominal parameters of a first-order RC (resistor-capacitor) model is determined, and the performance degradation of the nominal model over the battery lifetime is quantified. Second, two Extended Kalman Filters with different time scales are used for combined SOC/SOH monitoring: the SOC is estimated in real-time, and the SOH (the capacity and internal ohmic resistance) is updated offline. The time scale of the SOH estimator is determined based on model accuracy deterioration. The SOC and SOH estimation results are demonstrated by using large amounts of testing data over the battery lifetime. (C) 2014 The Authors. Published by Elsevier B.V.
引用
收藏
页码:793 / 803
页数:11
相关论文
共 50 条
  • [31] Modeling and state of charge estimation of lithium-ion battery
    Chen, Xi-Kun
    Sun, Dong
    ADVANCES IN MANUFACTURING, 2015, 3 (03) : 202 - 211
  • [32] Fast Estimation of State of Charge for Lithium-ion Battery
    Chen, Hung-Cheng
    Chou, Shuo-Rong
    Chen, Hong-Chou
    Wu, Shing-Lih
    Chen, Liang-Rui
    2014 INTERNATIONAL SYMPOSIUM ON COMPUTER, CONSUMER AND CONTROL (IS3C 2014), 2014, : 284 - 287
  • [33] Review of lithium-ion battery state of charge estimation
    Li, Ning
    Zhang, Yu
    He, Fuxing
    Zhu, Longhui
    Zhang, Xiaoping
    Ma, Yong
    Wang, Shuning
    GLOBAL ENERGY INTERCONNECTION-CHINA, 2021, 4 (06): : 619 - 630
  • [34] Optimized State of Charge Estimation of Lithium-Ion Battery in SMES/Battery Hybrid Energy Storage System for Electric Vehicles
    Sun, Qiang
    Lv, Haiying
    Wang, Shasha
    Gao, Shuang
    Wei, Kexin
    IEEE TRANSACTIONS ON APPLIED SUPERCONDUCTIVITY, 2021, 31 (08)
  • [35] Modeling and state of charge estimation of lithium-ion battery
    Xi-Kun Chen
    Dong Sun
    AdvancesinManufacturing, 2015, 3 (03) : 202 - 211
  • [36] Lithium-ion Battery Modeling and State of Charge Estimation
    Wei Xiong
    Mo, Yimin
    Feng Zhang
    INTEGRATED FERROELECTRICS, 2019, 200 (01) : 59 - 72
  • [37] A Combined DNN-NBEATS Architecture for State of Charge Estimation of Lithium-Ion Batteries in Electric Vehicles
    Kannan, M.
    Sundareswaran, Kinattingal
    Nayak, P. Srinivas Rao
    Simon, Sishaj P. P.
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2023, 72 (06) : 7328 - 7337
  • [38] State-of-charge Estimation for Lithium-ion Battery using a Combined Method
    Li, Guidan
    Peng, Kai
    Li, Bin
    JOURNAL OF POWER ELECTRONICS, 2018, 18 (01) : 129 - 136
  • [39] Methods for estimating lithium-ion battery state of charge for use in electric vehicles: A review
    Gaga A.
    Tannouche A.
    Mehdaoui Y.
    El Hadadi B.
    Energy Harvesting and Systems, 2022, 9 (02): : 211 - 225
  • [40] A Nonlinear-Model-Based Observer for a State-of-Charge Estimation of a Lithium-Ion Battery in Electric Vehicles
    Kim, Woo-Yong
    Lee, Pyeong-Yeon
    Kim, Jonghoon
    Kim, Kyung-Soo
    ENERGIES, 2019, 12 (17)