Control-Oriented Physics-Based Modeling and Observer Design for State-of-Charge Estimation of Lithium-Ion Cells for High Current Applications

被引:14
作者
Nath, Anirudh [1 ]
Mehta, Rohit [2 ]
Gupta, Raghvendra [2 ]
Bahga, Supreet Singh [2 ]
Gupta, Amit [2 ]
Bhasin, Shubhendu [1 ]
机构
[1] IIT Delhi, Dept Elect Engn, New Delhi 110016, India
[2] IIT Delhi, Dept Mech Engn, New Delhi 110016, India
关键词
Observers; Mathematical models; Computational modeling; Estimation; Electrodes; Electrolytes; Temperature measurement; Linear matrix inequality (LMI); lithium-ion cell; observer; single-particle model (SPM); state of charge (SoC); BATTERY-MANAGEMENT-SYSTEMS; ELECTROCHEMICAL MODEL; THERMAL-MODEL; PARTICLE; DIFFUSION; STRATEGY; PACKS;
D O I
10.1109/TCST.2022.3152446
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This article proposes a physics-based control-oriented model and observer design for the state-of-charge (SoC) estimation of lithium-ion cells for applications involving high magnitude fluctuating current profiles. The physics-based single-particle model (SPM) provides enhanced accuracy due to the inclusion of electrolyte dynamics and addresses the issue of nonobservability associated with it. The computationally efficient physics-based model is utilized to design a robust observer-based SoC estimator in the framework of linear matrix inequality to guarantee fast convergence despite parametric uncertainty in the state and output equations, and unknown initial conditions. The observer performance is validated using FTP75 and US06 dynamic tests at different temperatures, and the results are compared with the standard unscented Kalman filter (UKF). The mean SoC estimation error and the integral square error of the estimated SoC for the proposed observer are at least one order of magnitude smaller than that of UKF. Furthermore, robustness to +/- 30% parametric uncertainty, measurement noise, and unknown initial conditions is demonstrated through Monte Carlo simulations at different temperatures.
引用
收藏
页码:2466 / 2479
页数:14
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