Open circuit voltage and state of charge online estimation for lithium ion batteries
发表时间:2021-01-01     阅读次数:     字体:【


摘要:

Open circuit voltage (OCV), as a nonlinear function of state of charge (SoC) of lithium ion battery, commonly obtained through offline OCV test at certain ambient temperatures and aging stages. The OCV-SoC relationship may be inaccurate in real application due to the difference in operation conditions. In this paper, the OCV is identified by H infinity filter (HIF) in real operation conditions. Due to the no need to derive the jacobian matrices with unscented Kalman filter (UKF), the identified discrete OCV points are propagated to state estimation process instead of the traditional OCV-SoC nonlinear function. Additionally, the polarization voltage across the polarization capacitor is also passed to state estimation in the form of discrete data points. The experimental results demonstrate that the HIF-UKF can obtain the OCV and SoC in real time. (C) 2017 The Authors. Published by Elsevier Ltd.


部分图片:

图1 Schematic of the battery test bench

图2 UDDS profiles (a) Current (b) Reference SoC

引文信息

Xiong R , Yu Q , Wang L Y . Open circuit voltage and state of charge online estimation for lithium ion batteries[J]. Energy Procedia, 2017, 142:1902-1907. (下载链接)

其他相关论文

1. Xiong R, Yu Q, Lin C. A novel method to obtain the open circuit voltage for the state of charge of lithium ion batteries in electric vehicles by using H infinity filter[J]. Applied energy, 2017, 207: 346-353.(下载链接

2. Rui Xiong,Fengchun Sun,Zheng Chen,Hongwen He. A data-driven multi-scale extended Kalman filtering based parameter and state estimation approach of lithium-ion olymer battery in electric vehicles[J]. Applied Energy,2014,113. (下载链接)



上一篇:A study on the inflence of two OCV tests on state of charge estimation of lithium ion battery
下一篇:Lithium-Ion Battery Parameters and State-of-Charge Joint Estimation Based on H-Infinity and Unscented Kalman Filters
0
联系地址:北京市海淀区中关村南大街5号北京理工大学   Copyright  ©  2020-   先进储能科学与应用联合实验室  All Rights Reserved.网站地图
友情链接: 新能源与智能载运期刊    北京理工大学    机械与车辆学院