[1]刘新天,孙张驰,何耀,等.基于环境变量建模的锂电池SOC估计方法[J].东南大学学报(自然科学版),2017,47(2):306-312.[doi:10.3969/j.issn.1001-0505.2017.02.018]
 Liu Xintian,Sun Zhangchi,He Yao,et al.SOC estimation method based on lithium-ion cell model considering environmental factors[J].Journal of Southeast University (Natural Science Edition),2017,47(2):306-312.[doi:10.3969/j.issn.1001-0505.2017.02.018]
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基于环境变量建模的锂电池SOC估计方法()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
47
期数:
2017年第2期
页码:
306-312
栏目:
电气工程
出版日期:
2017-03-20

文章信息/Info

Title:
SOC estimation method based on lithium-ion cell model considering environmental factors
作者:
刘新天孙张驰何耀郑昕昕曾国建
合肥工业大学新能源汽车工程研究院, 合肥 230009
Author(s):
Liu Xintian Sun Zhangchi He Yao Zheng Xinxin Zeng Guojian
Clean Energy Automotive Research Institute, Hefei University of Technology, Hefei 230009, China
关键词:
动力锂电池 荷电状态 温度补偿 Thevenin模型 扩展卡尔曼滤波
Keywords:
power li-ion cell state-of-charge temperature compensation Thevenin model extended Kalman filter
分类号:
TM912
DOI:
10.3969/j.issn.1001-0505.2017.02.018
摘要:
通过对不同温度和锂电池荷电状态(SOC)下电池内部参数测定和评估,分析了影响参数变化的环境因素,建立了可变参数的锂电池Thevenin模型.讨论了模型的分段依据以及相关参数的测定和拟合方法,并采用扩展卡尔曼滤波算法(EKF)对锂电池SOC进行估算,给出了基于温度修正的改进SOC估计方法.所提出的电池模型解决了现有算法中模型适用范围局限性的问题,仿真和实验结果表明,所建立的基于锂电池Thevenin模型的SOC估计方法在较宽的温度范围内都能够获得较高的估算精度.
Abstract:
The internal parameters of the cell at different temperatures and state-of-charge(SOC)were tested and calculated. The factors affecting the variations of parameters were analyzed. The Thevenin model of the lithium-ion cell with variable parameters was established. The gist of segmentation and the method for determining the correlation parameters of the model were discussed. The extended Kalman filter(EKF)algorithm was used to estimate SOC. An improved SOC estimation method which is based on the temperature was given. The proposed cell model can avoid the application limitation of the existing models without considering the influences of environmental factors. Simulation and experimental results show that the SOC estimation method based on the established model can achieve higher accuracy in a wide temperature range.

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备注/Memo

备注/Memo:
收稿日期: 2016-06-05.
作者简介: 刘新天(1981—),男,博士,副研究员,xintian.liu@hfut.edu.cn.
基金项目: 国家自然科学基金资助项目(21373074)、安徽省国际科技合作计划资助项目(1303063010).
引用本文: 刘新天,孙张驰,何耀,等.基于环境变量建模的锂电池SOC估计方法[J].东南大学学报(自然科学版),2017,47(2):306-312. DOI:10.3969/j.issn.1001-0505.2017.02.018.
更新日期/Last Update: 2017-03-20