Structural Identifiability of a Pseudo-2D Li-ion Battery Electrochemical Model

被引:7
|
作者
Drummond, Ross [1 ]
Duncan, Stephen R. [1 ]
机构
[1] Univ Oxford, Dept Engn Sci, 17 Parks Rd, Oxford OX1 3PJ, England
来源
IFAC PAPERSONLINE | 2020年 / 53卷 / 02期
基金
英国工程与自然科学研究理事会;
关键词
Li-ion batteries; electrochemical models; structural identifiability;
D O I
10.1016/j.ifacol.2020.12.1328
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Growing demand for fast charging and optimised battery designs is fuelling significant interest in electrochemical models of Li-ion batteries. However, estimating parameter values for these models remains a major challenge. In this paper, a structural identifiability analysis was applied to a pseudo-2D Li-ion electrochemical battery model that can be considered as a linearised and decoupled form of the benchmark Doyle-Fuller-Newman model. From an inspection of the impedance function, it was shown that this model is uniquely parametrised by 21 parameters, being combinations of the electrochemical parameters like the conductivities and diffusion coefficients. The well-posedness of the parameter estimation problem with these parameters was then established. This result could lead to more realistic predictions about the internal state of the battery by identifying the parameter set that can be uniquely identified from the data. Copyright (C) 2020 The Authors.
引用
收藏
页码:12452 / 12458
页数:7
相关论文
共 50 条
  • [1] Assessment of Simplifications to a Pseudo-2D Electrochemical Model of Li-ion Batteries
    Kong, XiangRong
    Wetton, Brian
    Gopaluni, Bhushan
    IFAC PAPERSONLINE, 2019, 52 (01): : 946 - 951
  • [2] Identifiability Analysis of an Electrochemical Model of Li-ion Battery
    Samadi, M. Foad
    Saif, Mehrdad
    2016 AMERICAN CONTROL CONFERENCE (ACC), 2016, : 3107 - 3112
  • [3] PINN surrogate of Li-ion battery models for parameter inference, Part II: Regularization and application of the pseudo-2D model
    Hassanaly, Malik
    Weddle, Peter J.
    King, Ryan N.
    De, Subhayan
    Doostan, Alireza
    Randall, Corey R.
    Dufek, Eric J.
    Colclasure, Andrew M.
    Smith, Kandler
    JOURNAL OF ENERGY STORAGE, 2024, 98
  • [4] Parameter Identification for the Electrochemical Model of Li-ion Battery
    Shen, Wen-Jing
    Li, Han-Xiong
    2016 INTERNATIONAL CONFERENCE ON SYSTEM SCIENCE AND ENGINEERING (ICSSE), 2016,
  • [5] Simplification and efficient simulation of electrochemical model for Li-ion battery in EVs
    Lin, Cheng
    Tang, Aihua
    CLEAN ENERGY FOR CLEAN CITY: CUE 2016 - APPLIED ENERGY SYMPOSIUM AND FORUM: LOW-CARBON CITIES AND URBAN ENERGY SYSTEMS, 2016, 104 : 68 - 73
  • [6] Structural Identifiability of Equivalent Circuit Models for Li-Ion Batteries
    Grandjean, Thomas R. B.
    McGordon, Andrew
    Jennings, Paul A.
    ENERGIES, 2017, 10 (01)
  • [7] A TRACKING PROBLEM FOR THE STATE OF CHARGE IN A ELECTROCHEMICAL LI-ION BATTERY MODEL
    Hernandez, Esteban
    Prieur, Christophe
    Cerpa, Eduardo
    MATHEMATICAL CONTROL AND RELATED FIELDS, 2022, 12 (03) : 709 - 732
  • [8] PERFORMANCE EVALUATION OF AN EXTENDED KALMAN FILTER FOR STATE ESTIMATION OF A PSEUDO-2D THERMAL-ELECTROCHEMICAL LITHIUM-ION BATTERY MODEL
    Zhao, Shi
    Bizeray, Adrien M.
    Duncan, Stephen R.
    Howey, David A.
    PROCEEDINGS OF THE ASME 8TH ANNUAL DYNAMIC SYSTEMS AND CONTROL CONFERENCE, 2015, VOL 1, 2016,
  • [9] A Li-Ion Battery Discharge Model
    Chen, Liang-Rui
    Liu, Chuan-Sheng
    INTERNATIONAL REVIEW OF ELECTRICAL ENGINEERING-IREE, 2010, 5 (04): : 1769 - 1774
  • [10] ROBUST BAYESIAN SEQUENTIAL INPUT SHAPING FOR OPTIMAL LI-ION BATTERY MODEL PARAMETER IDENTIFIABILITY
    Rothenberger, Michael J.
    Fathy, Hosam K.
    PROCEEDINGS OF THE ASME 8TH ANNUAL DYNAMIC SYSTEMS AND CONTROL CONFERENCE, 2015, VOL 2, 2016,