An Improved Coulomb Counting Approach Based on Numerical Iteration for SOC Estimation With Real-Time Error Correction Ability

被引:32
|
作者
He, Liangzong [1 ]
Guo, Dong [1 ]
机构
[1] Univ Xiamen, Elect Engn Dept, Xiamen 361012, Fujian, Peoples R China
来源
IEEE ACCESS | 2019年 / 7卷
关键词
Improved coulomb counting (ICC); state of charge (SOC); accumulative error correction; numerical iteration; error accumulation rate; STATE-OF-CHARGE; LITHIUM-ION BATTERY; EXTENDED KALMAN FILTER; OBSERVER DESIGN; CO-ESTIMATION; MODEL; CAPACITY; IDENTIFICATION; MANAGEMENT;
D O I
10.1109/ACCESS.2019.2921105
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The coulomb counting (CC) approach is widely used in SOC estimation due to its simplicity and low calculation cost. However, in practical applications, the lack of error correction ability limits its accuracy due to the measured noise in the practical occasion. To address the issue, an improved CC (ICC) approach based on numerical iteration is proposed in this paper. In the proposed approach, a battery model based on a 2nd-order, RC circuit is first formulated to determine the SOC-OCV curve, R-OCV curve, and inner parameters. In the model, the slow dynamic and fast dynamic voltages are described separately, and are utilized for battery state assessment. Then, the SOC will be estimated by the CC approach at the unsteady state but through a numerical iteration approach at steady state. Consequently, the accumulative SOC error from the CC approach will be corrected when the numerical iteration approach is applied. Furthermore, a compensation coefficient is employed into the CC approach to reduce the error accumulation rate. Hence, the proposed ICC approach could make full use of the advantages of conventional CC in low computational demand and numerical iteration approach in error correction. Finally, an experiment platform was built, where two kinds of current sensors with different measuring accuracy were employed to simulate the measured current with and without noise, respectively. The experimental results suggest that the accumulative SOC error can be corrected in real-time and the SOC error is reduced to 1%. The error accumulation rate of SOC is effectively reduced compared with traditional CC approach, simultaneously, more than 90% of the calculation time can be reduced compared with EKF.
引用
收藏
页码:74274 / 74282
页数:9
相关论文
共 20 条
  • [1] Lithium-ion battery state of charge estimation using improved coulomb counting method with adaptive error correction
    Wu, King Hang
    Seyedmahmoudian, Mehdi
    Mekhilef, Saad
    Shrivastava, Prashant
    Stojcevski, Alex
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING, 2025, 239 (2-3) : 693 - 705
  • [2] Convergence Guarantees for Moving Horizon Estimation Based on the Real-Time Iteration Scheme
    Wynn, Andrew
    Vukov, Milan
    Diehl, Moritz
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2014, 59 (08) : 2215 - 2221
  • [3] An improved coulomb counting method based on non-destructive charge and discharge differentiation for the SOC estimation of NCM lithium-ion battery
    Zhu, Yucheng
    Xiong, Yonglian
    Xiao, Jie
    Yi, Ting
    Li, Chunsheng
    Sun, Yan
    JOURNAL OF ENERGY STORAGE, 2023, 73
  • [4] An improved coulomb counting method based on dual open-circuit voltage and real-time evaluation of battery dischargeable capacity considering temperature and battery aging
    Wang, Shun-Li
    Xiong, Xin
    Zou, Chuan-Yun
    Chen, Lei
    Jiang, Cong
    Xie, Yan-Xin
    Stroe, Daniel-Ioan
    INTERNATIONAL JOURNAL OF ENERGY RESEARCH, 2021, 45 (12) : 17609 - 17621
  • [5] Real-Time Model-Based Estimation of SOC and SOH for Energy Storage Systems
    Cacciato, Mario
    Nobile, Giovanni
    Scarcella, Giuseppe
    Scelba, Giacomo
    IEEE TRANSACTIONS ON POWER ELECTRONICS, 2017, 32 (01) : 794 - 803
  • [6] Real-time Model-based Estimation of SOC and SOH for Energy Storage Systems
    Cacciato, M.
    Nobile, G.
    Scarcella, G.
    Scelba, G.
    2015 IEEE 6TH INTERNATIONAL SYMPOSIUM ON POWER ELECTRONICS FOR DISTRIBUTED GENERATION SYSTEMS (PEDG), 2015, : 65 - 72
  • [7] LSTM-Based Real-Time SOC Estimation of Lithium-Ion Batteries Using a Vehicle Driving Simulator
    Kim, Si Jin
    Lee, Jong Hyun
    Wang, Dong Hun
    Lee, In Soo
    2021 21ST INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS 2021), 2021, : 618 - 622
  • [8] Real-time video streaming using prediction-based forward error correction
    Weng, Yung-Tsung
    Shih, Chi-Huang
    Kuo, Chun-I
    Shieh, Ce-Kuen
    COMPUTER NETWORKS, 2015, 92 : 134 - 147
  • [9] A totally coupled multi time-scale framework containing full parameters online identification and SOC real-time estimation of lithium-ion battery based on a fractional order model
    Wu, Shaojie
    Zhang, Shuzhi
    Li, Haoran
    Cao, Ganglin
    Hu, Zhaowei
    Yu, Yemao
    Zhang, Xiongwen
    JOURNAL OF ENERGY STORAGE, 2023, 73
  • [10] Research on Real-Time Optimized Operation and Dispatching Strategy for Integrated Energy System Based on Error Correction
    Zeng, Aidong
    Hao, Sipeng
    Ning, Jia
    Xu, Qingshan
    Jiang, Ling
    ENERGIES, 2020, 13 (11)