Model Order Reduction Techniques for Physics-Based Lithium-Ion Battery Management: A Survey

被引：52
作者：
Li, Yang [1 ]
Karunathilake, Dulmini [2 ]
Vilathgamuwa, D. Mahinda [3 ]
Mishra, Yateendra [2 ]
Farrell, Troy W. [4 ]
Choi, San Shing [5 ,6 ]
Zou, Changfu [7 ]
机构：
[1] Chalmers Univ Technol, Dept Elect Engn, S-41296 Gothenburg, Sweden
[2] Queensland Univ Technol, Sch Elect Engn & Robot, Brisbane, Qld 4001, Australia
[3] Queensland Univ Technol, Power Engn, Brisbane, Qld 4001, Australia
[4] Queensland Univ Technol, Sch Math Sci, Brisbane, Qld 4001, Australia
[5] Curtin Univ Technol, Perth, WA, Australia
[6] Queensland Univ Technol, Brisbane, Qld 4001, Australia
[7] Chalmers Univ Technol, Automat Control Grp, S-41296 Gothenburg, Sweden
来源：
IEEE INDUSTRIAL ELECTRONICS MAGAZINE | 2022年 / 16卷 / 03期
基金：
瑞典研究理事会; 欧盟地平线“2020”;
关键词：
Mathematical model; Electrodes; Integrated circuit modeling; Solids; Lithium-ion batteries; Electrolytes; Lithium; SINGLE-PARTICLE MODEL; ELECTROCHEMICAL MODEL; PREDICTIVE CONTROL; EQUIVALENT-CIRCUIT; PARAMETERS IDENTIFICATION; ORTHOGONAL COLLOCATION; CHARGE ESTIMATION; STATE ESTIMATION; SOC ESTIMATION; CELLS;
D O I：
10.1109/MIE.2021.3100318
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
To unlock the promise of electrified transportation and smart grids, emerging advanced battery management systems (BMSs) will play an important role in the health-aware monitoring, diagnosis, and control of lithium-ion (Li-ion) batteries (see 'Acronyms Used in This Article'). Sophisticated physics-based battery models incorporated into BMSs can offer valuable internal battery information to achieve improved operational safety, reliability, and efficiency and to extend the battery lifetimes. However, because they are developed from fundamental electrochemical and thermodynamic principles, rigorous physics-based models are saddled with exceedingly high cognitive and computational complexity for practical applications. © 2007-2011 IEEE.
引用
收藏
页码：36 / 51
页数：16
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