State of Charge Estimation of Lithium Ion Batteries Using an Extended Single Particle Model and Sigma-Point Kalman Filter

被引：0
|
作者：
Ngoc Tham Tran [1 ]
Vilathgamuwa, Mahinda [1 ]
Li, Yang [1 ]
Farrell, Troy [2 ]
Choi, San Shing [1 ]
Teague, Joseph [2 ]
机构：
[1] Queensland Univ Technol, Sch Elect Engn & Comp Sci, Brisbane, Qld, Australia
[2] Queensland Univ Technol, Sch Math Sci, Brisbane, Qld, Australia
来源：
2017 IEEE SOUTHERN POWER ELECTRONICS CONFERENCE (SPEC) | 2017年
基金：
澳大利亚研究理事会;
关键词：
Lithium ion cell; SOC estimation; extended single particle model; Sigma-point Kalman filter; ELECTROCHEMICAL MODEL; MANAGEMENT-SYSTEMS; DISCHARGE; CATHODES;
D O I：
暂无
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：
We present a method to estimate the state of charge (SOC) of lithium ion batteries using an extended single particle model (ESPM) and the sigma-point Kalman filter (SPKF) algorithm. ESPM is a computationally efficient battery electrochemical model while the SPKF algorithm allows the battery SOC to be estimated with high accuracy and stability. The proposed ESPM-SPKF method is stable, efficient and can be adopted for advanced battery management systems in large-scale battery energy storage systems.
引用
收藏
页码：405 / 410
页数：6
相关论文
共 50 条
  • [1] A Novel State-of-Charge Estimation Method for Lithium-ion Batteries Using Convolutional Transformer Network and Sigma-point Kalman Filter
    Duan, Yuxin
    Zou, Runmin
    2022 4TH INTERNATIONAL CONFERENCE ON SMART POWER & INTERNET ENERGY SYSTEMS, SPIES, 2022, : 1850 - 1855
  • [2] State of Charge Estimation of Lithium-ion Batteries Electrochemical Model with Extended Kalman Filter
    Liu, Yuntian
    Huangfu, Yigeng
    Ma, Rui
    Xu, Liangcai
    Zhao, Dongdong
    Wei, Jiang
    2019 IEEE INDUSTRY APPLICATIONS SOCIETY ANNUAL MEETING, 2019,
  • [3] State-of-charge Estimation of Lithium-ion Batteries Using Extended Kalman Filter
    Rezoug, Mohamed Redha
    Taibi, Djamel
    Benaouadj, Mahdi
    2021 10TH INTERNATIONAL CONFERENCE ON POWER SCIENCE AND ENGINEERING (ICPSE 2021), 2021, : 98 - 103
  • [4] State-of-Charge Estimation of Lithium-ion Batteries using Extended Kalman filter and Unscented Kalman filter
    Jokic, Ivan
    Zecevic, Zarko
    Krstajic, Bozo
    2018 23RD INTERNATIONAL SCIENTIFIC-PROFESSIONAL CONFERENCE ON INFORMATION TECHNOLOGY (IT), 2018,
  • [5] An online model identification for state of charge estimation of lithium-ion batteries using extended kalman filter
    Zhao, Guangming
    Wang, Yifan
    2020 IEEE 3RD INTERNATIONAL CONFERENCE ON RENEWABLE ENERGY AND POWER ENGINEERING (REPE), 2020, : 34 - 38
  • [6] State of Charge Estimation for Lithium-Ion Batteries Based on Extended Kalman Particle Filter and Orthogonal Optimized Battery Model
    Shi, Shuaiwei
    Zhang, Minshu
    Lu, Mi
    Wu, Changfeng
    Cai, Xiang
    ADVANCED THEORY AND SIMULATIONS, 2024, 7 (05)
  • [7] State of Charge Estimation of the Lithium-Ion Battery Pack Based on Two Sigma-Point Kalman Filters
    Nguyen Vinh Thuy
    Nguyen Van Chi
    Ngo Minh Duc
    Nguyen Hong Quang
    NEXT GENERATION OF INTERNET OF THINGS, 2023, 445 : 427 - 442
  • [8] Differential voltage analysis based state of charge estimation methods for lithium-ion batteries using extended Kalman filter and particle filter
    Zheng, Linfeng
    Zhu, Jianguo
    Wang, Guoxiu
    Lu, Dylan Dah-Chuan
    He, Tingting
    ENERGY, 2018, 158 : 1028 - 1037
  • [9] Sigma-Point Kalman Filter with State Constraints
    Schneider, Paul
    Janocha, Hartmut
    AT-AUTOMATISIERUNGSTECHNIK, 2009, 57 (04) : 169 - 176
  • [10] A novel method for state of energy estimation of lithium-ion batteries using particle filter and extended Kalman filter
    Lai, Xin
    Huang, Yunfeng
    Han, Xuebing
    Gu, Huanghui
    Zheng, Yuejiu
    JOURNAL OF ENERGY STORAGE, 2021, 43
12345