eXogenous Kalman Filter for State-of-Charge Estimation in Lithium-Ion Batteries

被引：0
|
作者：
Hasan, Agus [1 ]
Skriver, Martin [1 ]
Johansen, Tor Arne [2 ]
机构：
[1] Univ Southern Denmark, Maersk McKinney Moller Inst, Ctr Unmanned Aerial Syst, Odense, Denmark
[2] Norwegian Univ Sci & Technol, Dept Cybernet Engn, Trondheim, Norway
来源：
2018 IEEE CONFERENCE ON CONTROL TECHNOLOGY AND APPLICATIONS (CCTA) | 2018年
关键词：
OPEN-CIRCUIT VOLTAGE; BOUNDARY OBSERVER; MODELS;
D O I：
暂无
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 paper presents State-of-Charge (SoC) estimation of lithium-ion batteries using eXogenous Kalman filter (XKF). The state-space equation for the lithium-ion battery is obtained from the equivalent circuit model (ECM). It has linear process equations and a nonlinear output voltage equation. The estimation is done using a cascade of nonlinear observer and a linearized Kalman filter. The method is tested using experimental data of a lithium-ion-phosphate (LiFePO4) battery under dynamic stress test (DST) and federal urban driving schedule (FUDS). The results are compared with existing Kalman filters.
引用
收藏
页码：1403 / 1408
页数：6
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