An improved coulomb counting method based on non-destructive charge and discharge differentiation for the SOC estimation of NCM lithium-ion battery

被引:15
作者
Zhu, Yucheng [1 ]
Xiong, Yonglian [1 ,2 ]
Xiao, Jie [1 ]
Yi, Ting [1 ,2 ]
Li, Chunsheng [3 ,4 ]
Sun, Yan [3 ,4 ]
机构
[1] Yancheng Inst Technol, Coll Automot Engn, Yancheng 224051, Jiangsu, Peoples R China
[2] New Energy Sci & Energy Storage Engn Technol Res C, Yancheng 224051, Jiangsu, Peoples R China
[3] Suzhou Univ Sci & Technol, Sch Chem & Life Sci, Suzhou 215009, Jiangsu, Peoples R China
[4] Suzhou Univ Sci & Technol, Key Lab Adv Electrode Mat Novel Solar Cells Petr &, Suzhou 215009, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
Coulomb counting method; State of charge; Non-destructive charge and discharge; differentiation; NCM battery; OBSERVER; MODEL; STATE;
D O I
10.1016/j.est.2023.108917
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
Accurate state of charge (SOC) estimation plays a crucial role in the safe and efficient operation of batteries. The coulomb counting (CC) approach has been used extensively in industrial production as a relatively easy-to-use and reliable algorithm for estimating battery SOC. However, the accuracy of standard CC method is constrained and it cannot satisfy some complex operating environment requirements. In this paper, a CC approach based on non-destructive charge and discharge differentiation is proposed on NCM battery. This method corrects the battery's initial SOC value using the open-circuit voltage method. It also corrects the actual capacity of the battery based on temperature, discharge rate and aging. Finally, it corrects the CC method's cumulative error using non-destructive capacity differentiation (dQ/dV) and voltage differentiation (dV/dQ). Experimental results show the maximum estimation error of the proposed approach is 3.33 % in the temperature range of -10 degrees C to 45 degrees C which is 15.57 % lower than the traditional OCV - CC method at -10 degrees C.
引用
收藏
页数:11
相关论文
共 31 条
  • [21] A comprehensive review of battery state of charge estimation techniques
    Ul Hassan, Masood
    Saha, Sajeeb
    Haque, Md. Enamul
    Islam, Shama
    Mahmud, Apel
    Mendis, Nishad
    [J]. SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS, 2022, 54
  • [22] 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
    [J]. INTERNATIONAL JOURNAL OF ENERGY RESEARCH, 2021, 45 (12) : 17609 - 17621
  • [23] State of charge estimation for lithium-ion batteries using dynamic neural network based on sine cosine algorithm
    Wei, Meng
    Ye, Min
    Li, Jia Bo
    Wang, Qiao
    Xu, Xin Xin
    [J]. PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING, 2022, 236 (2-3) : 241 - 252
  • [24] Online state-of-charge estimation refining method for battery energy storage system using historical operating data
    Xiao, Lizhong
    Li, Xining
    Jiang, Quanyuan
    Geng, Guangchao
    [J]. JOURNAL OF ENERGY STORAGE, 2023, 57
  • [25] State of Charge Estimation of Lithium-Ion Battery Based on Improved Adaptive Unscented Kalman Filter
    Xing, Jie
    Wu, Peng
    [J]. SUSTAINABILITY, 2021, 13 (09)
  • [26] Parameter identification and SOC estimation for power battery based on multi-timescale double Kalman filter algorithm
    Xing, Likun
    Zhan, Mingrui
    Guo, Min
    Ling, Liuyi
    [J]. INTERNATIONAL JOURNAL OF COMPUTATIONAL SCIENCE AND ENGINEERING, 2022, 25 (06) : 619 - 628
  • [27] An improved state of charge estimation of lithium-ion battery based on a dual input model
    Xiong, Yonglian
    Zhu, Yucheng
    Xing, Houchao
    Lin, Shengqiang
    Xiao, Jie
    Zhang, Chi
    Yi, Ting
    Fan, Yongsheng
    [J]. ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS, 2023, 45 (01) : 575 - 588
  • [28] Adaptive State-of-Charge Estimation for Lithium-Ion Batteries by Considering Capacity Degradation
    Xu, Peipei
    Li, Junqiu
    Sun, Chao
    Yang, Guodong
    Sun, Fengchun
    [J]. ELECTRONICS, 2021, 10 (02) : 1 - 17
  • [29] Incremental capacity analysis and differential voltage analysis based state of charge and capacity estimation for lithium-ion batteries
    Zheng, Linfeng
    Zhu, Jianguo
    Lu, Dylan Dah-Chuan
    Wang, Guoxiu
    He, Tingting
    [J]. ENERGY, 2018, 150 : 759 - 769
  • [30] A Method to Identify Lithium Battery Parameters and Estimate SOC Based on Different Temperatures and Driving Conditions
    Zheng, Yongliang
    He, Feng
    Wang, Wenliang
    [J]. ELECTRONICS, 2019, 8 (12)