Estimation and Fault Diagnosis of Lithium-Ion Batteries: A Fractional-Order System Approach

被引:5
|
作者
Kong, Shulan [1 ]
Saif, Mehrdad [2 ]
Cui, Guozeng [3 ]
机构
[1] Qufu Normal Univ, Sch Math Sci, Qufu 273165, Peoples R China
[2] Univ Windsor, Dept Elect & Comp Engn, Windsor, ON N9B 3P4, Canada
[3] Suzhou Univ Sci & Technol, Sch Elect & Informat Engn, Suzhou 215009, Peoples R China
基金
中国国家自然科学基金;
关键词
OBSERVER DESIGN; STATE; STABILITY; VARIABLES;
D O I
10.1155/2018/8705363
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This study investigates estimation and fault diagnosis of fractional-order Lithium-ion battery system. Two simple and common types of observers are designed to address the design of fault diagnosis and estimation for the fractional-order systems. Fractional-order Luenberger observers are employed to generate residuals which are then used to investigate the feasibility of model based fault detection and isolation. Once a fault is detected and isolated, a fractional-order sliding mode observer is constructed to provide an estimate of the isolated fault. The paper presents some theoretical results for designing stable observers and fault estimators. In particular, the notion of stability in the sense of Mittag-Leffler is first introduced to discuss the state estimation error dynamics. Overall, the design of the Luenberger observer as well as the sliding mode observer can accomplish fault detection, fault isolation, and estimation. The effectiveness of the proposed strategy on a three-cell battery string system is demonstrated.
引用
收藏
页数:12
相关论文
共 50 条
  • [1] A fractional-order KiBaM of lithium-ion batteries with capacity nonlinearity
    Zhang, Qi
    Shang, Yunlong
    Cui, Naxin
    Li, Yan
    Zhang, Chenghui
    [J]. 2017 CHINESE AUTOMATION CONGRESS (CAC), 2017, : 4995 - 5000
  • [2] Fractional-order modeling and parameter identification for lithium-ion batteries
    Wang, Baojin
    Li, Shengbo Eben
    Peng, Huei
    Liu, Zhiyuan
    [J]. JOURNAL OF POWER SOURCES, 2015, 293 : 151 - 161
  • [3] Adaptive state of charge estimation for lithium-ion batteries based on implementable fractional-order technology
    Li, Shizhong
    Li, Yan
    Zhao, Daduan
    Zhang, Chenghui
    [J]. JOURNAL OF ENERGY STORAGE, 2020, 32
  • [4] Estimation for state of charge of lithium-ion batteries by adaptive fractional-order unscented Kalman filters
    Miao, Yue
    Gao, Zhe
    [J]. JOURNAL OF ENERGY STORAGE, 2022, 51
  • [5] State-of-charge estimation for lithium-ion batteries based on incommensurate fractional-order observer
    Chen, Liping
    Guo, Wenliang
    Lopes, Antonio M.
    Wu, Ranchao
    Li, Penghua
    Yin, Lisheng
    [J]. COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2023, 118
  • [6] Parameter Sensitivity Analysis for Fractional-Order Modeling of Lithium-Ion Batteries
    Zhou, Daming
    Zhang, Ke
    Ravey, Alexandre
    Gao, Fei
    Miraoui, Abdellatif
    [J]. ENERGIES, 2016, 9 (03)
  • [7] State of Charge Estimation of Lithium-Ion Batteries Based on Fuzzy Fractional-Order Unscented Kalman Filter
    Chen, Liping
    Chen, Yu
    Lopes, Antonio M.
    Kong, Huifang
    Wu, Ranchao
    [J]. FRACTAL AND FRACTIONAL, 2021, 5 (03)
  • [8] State of Charge Estimation for Lithium-Ion Batteries Based on an Adaptive Fractional-Order Cubature Kalman Filter
    Chai, Haoyu
    Gao, Zhe
    Miao, Yue
    Jiao, Zhiyuan
    [J]. ADVANCED THEORY AND SIMULATIONS, 2023, 6 (07)
  • [9] State-of-health diagnosis of lithium-ion batteries using the fractional-order electrochemical impedance model
    Laribi, Slimane
    Arama, Fatima Zohra
    Mammar, Khaled
    Aoun, Nouar
    Ghaitaoui, Touhami
    Hamouda, Messaoud
    [J]. MEASUREMENT, 2023, 211
  • [10] Nonlinear Fractional-Order Estimator With Guaranteed Robustness and Stability for Lithium-Ion Batteries
    Zou, Changfu
    Hu, Xiaosong
    Dey, Satadru
    Zhang, Lei
    Tang, Xiaolin
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2018, 65 (07) : 5951 - 5961