The Lithium-Ion Battery Capacity Prediction Error Analysis Based on Extended Kalman Filtering

被引：0
|
作者：
Zhou, Zhenwei [1 ]
Huang, Yun [1 ]
Lu, Yudong [1 ]
Shi, Zhengyu [1 ]
Zhu, Liangbiao [1 ]
Wu, Jiliang [2 ]
Li, Hui [2 ]
机构：
[1] China Elect Prod Reliabil & Environm Testing Res, Guangzhou, Guangdong, Peoples R China
[2] Wuhan Zhongyuan Changjiang River Sci Dev Ltd, Wuhan, Hubei, Peoples R China
来源：
PROCEEDINGS OF 2014 10TH INTERNATIONAL CONFERENCE ON RELIABILITY, MAINTAINABILITY AND SAFETY (ICRMS), VOLS I AND II | 2014年
关键词：
Lithiun-ion battery; capacity; prediction erro; extended Kalman filtering; curve fitting;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
The Lithium-ion battery capacity prediction error is analyzed by use of extended Kalman filtering(EKF) and curve fitting algorithms. This paper employs the capacity degradation model described by Colum efficient factor, rest time and other two unknown parameters. Then, a nonlinear state-space model is introduced, and the EKF is presented to estimate the capacity and the two unknown parameters. The parameter setting in EKF is discussed in details. The capacity prediction error is analyzed with the help of curve fitting. The experiment example demonstrates the algorithms efficiency.
引用
收藏
页码：252 / 256
页数：5
相关论文
共 50 条
  • [1] The End of Discharge prediction of the Lithium-Ion battery with improved model based on Particle Filtering
    Obkit, Rattanaprasit
    Yu, Jinsong
    Tang, Diyin
    Liu, Hao
    2018 IEEE CSAA GUIDANCE, NAVIGATION AND CONTROL CONFERENCE (CGNCC), 2018,
  • [2] Online prediction for heat generation rate and temperature of lithium-ion battery using multi-step-ahead extended Kalman filtering
    Lyu, Chao
    Song, Yankong
    Yang, Dazhi
    Wang, Wenting
    Ge, Yaming
    Wang, Lixin
    APPLIED THERMAL ENGINEERING, 2023, 231
  • [3] Prediction of lithium-ion battery capacity with metabolic grey model
    Chen, Lin
    Lin, Weilong
    Li, Junzi
    Tian, Binbin
    Pan, Haihong
    ENERGY, 2016, 106 : 662 - 672
  • [4] Modeling and Simulation for Capacity Fade Prediction of Lithium-Ion Battery
    Bairwa, Bansilal
    Hampannavar, Santoshkumar
    Vishal, Kaushik S.
    Bhargavi, K. M.
    IEEE EUROCON 2021 - 19TH INTERNATIONAL CONFERENCE ON SMART TECHNOLOGIES, 2021, : 537 - 541
  • [5] A criterion combined of bulk and surface lithium storage to predict the capacity of porous carbon lithium-ion battery anodes: lithium-ion battery anode capacity prediction
    Majid Shaker
    Ali Asghar Sadeghi Ghazvini
    Faisal Raza Qureshi
    Reza Riahifar
    Carbon Letters, 2021, 31 : 985 - 990
  • [6] Lithium-Ion Battery Capacity Prediction Method Based on Improved Extreme Learning Machine
    Liu, Zhengyu
    Huang, Zaijun
    Tang, Liandong
    Wang, Hao
    JOURNAL OF ELECTROCHEMICAL ENERGY CONVERSION AND STORAGE, 2025, 22 (01)
  • [7] A criterion combined of bulk and surface lithium storage to predict the capacity of porous carbon lithium-ion battery anodes: lithium-ion battery anode capacity prediction
    Shaker, Majid
    Ghazvini, Ali Asghar Sadeghi
    Qureshi, Faisal Raza
    Riahifar, Reza
    CARBON LETTERS, 2021, 31 (05) : 985 - 990
  • [8] An improved adaptive unscented kalman filtering for state of charge online estimation of lithium-ion battery
    Zhang, Shuzhi
    Guo, Xu
    Zhang, Xiongwen
    JOURNAL OF ENERGY STORAGE, 2020, 32
  • [9] Capacity prediction of lithium-ion battery using UKF based on different C-rate
    Kim, Gunwoo
    Sin, Seunghwa
    Park, Jinhyung
    Baek, Insu
    Baek, Jongbok
    Kim, Jonghoon
    2021 24TH INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES AND SYSTEMS (ICEMS 2021), 2021, : 2303 - 2306
  • [10] A novel voltage matching-adaptive extended Kalman filtering construction method for the state of charge prediction of lithium-ion batteries
    Shi, Weihao
    Wang, Shunli
    Xia, Lili
    Yu, Peng
    Li, Bowen
    TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL, 2021,
12345