荷电状态
稳健性(进化)
内阻
阳极
控制理论(社会学)
电压
电池(电)
锂离子电池
计算机科学
观察员(物理)
等效电路
工程类
电子工程
电气工程
电极
化学
功率(物理)
控制(管理)
物理
物理化学
人工智能
基因
量子力学
生物化学
作者
Domenico Natella,Simona Onori,Francesco Vasca
出处
期刊:IEEE Transactions on Industrial Electronics
[Institute of Electrical and Electronics Engineers]
日期:2022-01-01
卷期号:70 (6): 5760-5770
被引量:1
标识
DOI:10.1109/tie.2022.3194576
摘要
Aging and usage conditions affect the battery parameters such as capacity and changes in the open-circuit voltage and internal resistance dependencies on the state of charge. This paper proposes an on-board strategy for the simultaneous estimation of these parameters and their robust evaluation during the battery life. The proposed co-estimation framework consists of a set of interconnected subsystems grounded on the integration of recursive least-squares techniques and a Luenberger-like observer which are independently designed by relying on moving averages of voltage and current measurements. Each subsystem is separately activated through logic variables which select the operating conditions proper for the estimation purposes and allows tracking of model parameters variations. The effectiveness of the solution is shown over experiments with a cylindrical LG M50T INR21700 Li-ion cell with NMC cathode and graphite/silicon anode.
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