Estimation on state of charge of power battery based on rebound voltage

被引:0
|
作者
Chen, Lun-Qiong [1 ]
Du, Lu-Lu [2 ]
Li, Bei [1 ]
机构
[1] Changzhou Institute of Technology, School of Electronic Information and Electrical Engineering, Changzhou, China
[2] WuWei Occupational College, School of Electronic Information, Wuwei, China
关键词
Battery management systems - Charging (batteries) - Secondary batteries - Forecasting;
D O I
暂无
中图分类号
TM912 [蓄电池];
学科分类号
摘要
This paper proposed a measuring parameter rebound voltage to realize real-time accurate estimation for state of charge (SOC) of power battery. On the basis of experimental data of SOC, rebound voltage and discharge current, a method which combined the features of grey prediction model and BP neural network prediction model was used to predict the data of SOC. By comparing the prediction data with practical data, the grey neural network method can achieve less error and the prediction accuracy is improved significantly. © Sila Science. All rights reserved.
引用
收藏
页码:6531 / 6538
相关论文
共 50 条
  • [1] A Novel Battery State of Charge Estimation Based on Voltage Relaxation Curve
    Lee, Suhyeon
    Lee, Dongho
    BATTERIES-BASEL, 2023, 9 (10):
  • [2] Power battery state of charge estimation based on extended Kalman filter
    Wang, Qi
    Feng, Xiaoyi
    Zhang, Bo
    Gao, Tian
    Yang, Yan
    JOURNAL OF RENEWABLE AND SUSTAINABLE ENERGY, 2019, 11 (01)
  • [3] State of charge and state of power estimation for power battery in HEV based on optimized particle filtering
    Niu, Xiaoyan
    Feng, Guosheng
    JOURNAL OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING, 2021, 21 (02) : 257 - 276
  • [4] Control of Solar System's Battery Voltage Based on State of Charge Estimation (SOC)
    Hajizadeh, Amin
    Shahirinia, Amir Hossein
    Arabameri, Saeed
    Yu, David C.
    2014 INTERNATIONAL CONFERENCE ON RENEWABLE ENERGY RESEARCH AND APPLICATION (ICRERA), 2014, : 162 - 167
  • [5] State of Charge Estimation of Power Lithium Battery Based on Extended Kalman Filter
    Feng, Huizong
    Qin, Liangyan
    Xu, Yang
    2019 CHINESE AUTOMATION CONGRESS (CAC2019), 2019, : 518 - 523
  • [6] Research on State of Charge Estimation for Power Battery of Electric Vehicle
    Zong, Changfu
    Xiang, Haiou
    He, Lei
    Chen, Dongxue
    INDUSTRIAL INSTRUMENTATION AND CONTROL SYSTEMS II, PTS 1-3, 2013, 336-338 : 799 - 803
  • [7] State of Charge Estimation of Battery in Low Power States Based on Chaotic Neural Network
    Li, Jianhua
    Liu, Mingsheng
    Wen, Hongnian
    Xu, Aixue
    2ND INTERNATIONAL CONFERENCE ON GREEN ENERGY AND SUSTAINABLE DEVELOPMENT (GESD 2019), 2019, 2122
  • [8] State of Charge Imbalance Estimation for Battery Strings Under Reduced Voltage Sensing
    Lin, Xinfan
    Stefanopoulou, Anna G.
    Li, Yonghua
    Anderson, R. Dyche
    IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2015, 23 (03) : 1052 - 1062
  • [9] Battery State-of-Charge Estimation Prototype using EMF Voltage Prediction
    Unterrieder, Christoph
    Lunglmayr, Michael
    Marsili, Stefano
    Huemer, Mario
    2014 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS), 2014, : 622 - 625
  • [10] A linear recursive state of power estimation method based on fusion model of voltage and state of charge limitations
    Li, Bowen
    Wang, Shunli
    Fernandez, Carlos
    Yu, Chunmei
    Xia, Lili
    Fan, Yongcun
    JOURNAL OF ENERGY STORAGE, 2021, 40