A parameter estimation method for a simplified electrochemical model for Li-ion batteries

被引：72

作者：

Li, Junfu ^{[1
]}

Wang, Lixin ^{[2
]}

Lyu, Chao ^{[1
]}

Liu, Enhui ^{[2
]}

Xing, Yinjiao ^{[3
]}

Pecht, Michael ^{[3
]}

机构：

[1] Harbin Inst Technol, Sch Elect Engn & Automat, Harbin 150001, Heilongjiang, Peoples R China

[2] Harbin Inst Technol, Sch Electromech Engn & Automat, Shenzhen 518055, Peoples R China

[3] Univ Maryland, CALCE, College Pk, MD 20742 USA

来源：

ELECTROCHIMICA ACTA | 2018年 / 275卷

基金：

中国国家自然科学基金;

关键词：

Battery management system; Model parameters; Electrochemical model; Operating test; SINGLE-PARTICLE MODEL; GENETIC ALGORITHM APPROACH; CHARGE-DISCHARGE RATES; ORTHOGONAL COLLOCATION; THERMAL-BEHAVIOR; INSERTION CELL; LITHIUM; DIFFUSION; IDENTIFICATION; OPTIMIZATION;

D O I：

10.1016/j.electacta.2018.04.098

中图分类号：

O646 [电化学、电解、磁化学];

学科分类号：

081704 ;

摘要：

Traditional electrochemical algorithms are too complex for use in real-time battery management systems (BMSs). Determination of parameters and implementation of algorithms are the key challenges for electrochemical models for Li-ion batteries. This paper develops a simplified electrochemical model that incorporates open-circuit voltage, liquid-phase diffusion, reaction polarization, and ohmic polarization, and uses a fast operating test to identify all the parameters to solve these challenges. The model is then implemented and compared against experimental measurements. Validations of parameter estimation and charge/discharge behaviors indicate that the developed parameter estimation method for the electrochemical model is effective. With this model and parameter estimation technique, electrochemical model-based state of charge (SOC) estimation can be realized online and can provide accurate results. (c) 2018 Elsevier Ltd. All rights reserved.

引用

页码：50 / 58

页数：9

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