An Improved Rainflow Algorithm Combined with Linear Criterion for the Accurate Li-ion Battery Residual Life Prediction

被引:6
|
作者
Huang, Junhan [1 ]
Wang, Shunli [1 ]
Xu, Wenhua [1 ]
Fernandez, Carlos [2 ]
Fan, Yongcun [1 ]
Chen, Xianpei [1 ]
机构
[1] Southwest Univ Sci & Technol, Sch Informat Engn, Mianyang 621010, Sichuan, Peoples R China
[2] Robert Gordon Univ, Sch Pharm & Life Sci, Aberdeen AB10 7GJ, Scotland
来源
基金
中国国家自然科学基金;
关键词
Li-ion battery; state of charge; unscented Kalman filtering; Rainflow; linear prediction criterion; HIGH-ENERGY-DENSITY; LITHIUM; STATE; MODEL; SOC;
D O I
10.20964/2021.07.29
中图分类号
O646 [电化学、电解、磁化学];
学科分类号
081704 ;
摘要
Li-ion battery health assessment has been widely used in electric vehicles, unmanned aerial vehicle and other fields. In this paper, a new linear prediction method is proposed. By weakening the sensitivity of the Rainflow algorithm to the peak data, it can be applied to the field of battery, and can accurately count the number of Li-ion battery cycles, and skip the cumbersome link of parameter identification. Then, a linear criterion is proposed based on the idea of proportion, which makes the life prediction of Li-ion battery linear. Under the verification of multiple sets of data, the prediction error of this method is kept within 2.53%. This method has the advantages of high operation efficiency and simple operation, which provides a new idea for battery life prediction in the field of electric vehicles and aerospace.
引用
收藏
页码:1 / 15
页数:15
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