Please wait a minute...
材料导报  2019, Vol. 33 Issue (Z2): 53-55    
  无机非金属及其复合材料 |
基于BP神经网络法研究锂电池荷电状态
杨学平1, 王正江2, 蒋超宇1, 薛秀丽1
1 云南机电职业技术学院,昆明 650203;
2 昆明理工大学,昆明 650203
State of Charge of Lithium-ion Battery Based on BP Neural Network
YANG Xueping1, WANG Zhengjiang2, JIANG Chaoyu1, XUE Xiuli1
1 Yunnan Vocational College of Mechanical and Electrical Technology, Kunming 650203;
2 Kunming University of Science and Technology, Kunming 650203
下载:  全 文 ( PDF ) ( 1690KB ) 
输出:  BibTeX | EndNote (RIS)      
摘要 电动汽车锂离子动力电池荷电估算是电池管理系统的关键技术之一,电池荷电状态的精准计算对于电动汽车的续航里程估计有着重要意义。选取某车型三元锂离子动力电池组为研究对象,在指定温度下利用专用动力电池数据采集仪器采集动力电池数据,然后将数据植入到BP神经网络模型中去学习训练与验证。结果表明:基于BP神经网络法计算电池荷电的误差基本能控制在6%以内,验证了模型的准确性,为电池荷电估计算法的研究与改进打下了坚实的基础。
服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
杨学平
王正江
蒋超宇
薛秀丽
关键词:  BP神经网络  电动汽车  锂离子动力电池  荷电状态    
Abstract: It is one of the key technologies of battery management system to estimate the charge of lithium-ion battery in electric vehicle and accurately estimating the state of charge of batteries is of great significance to the estimation of the endurance mileage of electric vehicles.The three element lithium ion power battery pack was selected as the research object and the data of the power battery were collected by the special power battery data acquisition instrument in the specified temperature. Then the data was implanted into the BP neural network model to learn training and validate.The validation results showed that the error of SOC can be controlled within 6％ by the BP nature network method.The accuracy of the model was verified, which provided solid foundation for SOC estimation algorithm.
Key words:  BP nature network    electric vehicle    lithium-ion power battery    state of charge (SOC)
               出版日期:  2019-11-25      发布日期:  2019-11-25
ZTFLH:  TM911  
基金资助: 青年骨干教师科研项目(2017QN09)
通讯作者:  415417544@qq.com   
作者简介:  杨学平,云南机电职业技术学院讲师。2014年7月在昆明理工大学车辆工程专业取得硕士学位,主要从事汽车新能源技术研究工作。
引用本文:    
杨学平, 王正江, 蒋超宇, 薛秀丽. 基于BP神经网络法研究锂电池荷电状态[J]. 材料导报, 2019, 33(Z2): 53-55.
YANG Xueping, WANG Zhengjiang, JIANG Chaoyu, XUE Xiuli. State of Charge of Lithium-ion Battery Based on BP Neural Network. Materials Reports, 2019, 33(Z2): 53-55.
链接本文:  
http://www.mater-rep.com/CN/  或          http://www.mater-rep.com/CN/Y2019/V33/IZ2/53
1 王志福,彭连云,孙逢春,等.电池,2003,33(3),167.
2 华周发,李静.电源技术,2013,37(9),1686.
3 项宇,刘春光,苏建强,等.电源技术,2013,37(6),963.
4 张传伟,李林阳,赵东刚.电源技术,2017,41(9),1356.
5 史峰,王小川,郁磊,等.MATLAB神经网络30个案例分析.北京航空航天大学出版社,2011,1.
6 封进.电源技术,2016,40(2),283.
7 孔祥创,赵万忠,王春燕.汽车工程,2017,39(6),648.
8 冷炎.基于CKF的锂电池SOC估算及其电池管理系统研究.硕士学位论文,江苏大学,2016.
9 刘征宇,杨俊斌,张庆,等.电子测量与仪器学报,2013,27(3),224.
10 金周,詹元杰,陈宇阳,等.储能科学与技术,2018,7(2),175.
[1] 李地红, 高群, 夏娴, 张景卫, 于海洋, 王艳君, 代函函, 许国栋. 基于BP神经网络的混凝土综合性能预测[J]. 材料导报, 2019, 33(Z2): 317-320.
[2] 李红, 刘旭升, 张宜生, JacekSenkara, 李光瀛, 马鸣图. 新能源电动汽车异种材料连接技术的挑战、趋势和进展[J]. 材料导报, 2019, 33(23): 3853-3861.
[3] 董越, 杨志强, 高谦. 正交试验协同BP神经网络模型预测充填体强度[J]. 材料导报, 2018, 32(6): 1032-1036.
[1] Dongyong SI, Guangxu HUANG, Chuanxiang ZHANG, Baolin XING, Zehua CHEN, Liwei CHEN, Haoran ZHANG. Preparation and Electrochemical Performance of Humic Acid-based Graphitized Materials[J]. Materials Reports, 2018, 32(3): 368 -372 .
[2] Bingwei LUO,Dabo LIU,Fei LUO,Ye TIAN,Dongsheng CHEN,Haitao ZHOU. Research on the Two Typical Infrared Detection Materials Serving at Low Temperatures: a Review[J]. Materials Reports, 2018, 32(3): 398 -404 .
[3] Huimin PAN,Jun FU,Qingxin ZHAO. Sulfate Attack Resistance of Concrete Subjected to Disturbance in Hardening Stage[J]. Materials Reports, 2018, 32(2): 282 -287 .
[4] Siyuan ZHOU,Jianfeng JIN,Lu WANG,Jingyi CAO,Peijun YANG. Multiscale Simulation of Geometric Effect on Onset Plasticity of Nano-scale Asperities[J]. Materials Reports, 2018, 32(2): 316 -321 .
[5] Xu LI,Ziru WANG,Li YANG,Zhendong ZHANG,Youting ZHANG,Yifan DU. Synthesis and Performance of Magnetic Oil Absorption Material with Rice Chaff Support[J]. Materials Reports, 2018, 32(2): 219 -222 .
[6] Ninghui LIANG,Peng YANG,Xinrong LIU,Yang ZHONG,Zheqi GUO. A Study on Dynamic Compressive Mechanical Properties of Multi-size Polypropylene Fiber Concrete Under High Strain Rate[J]. Materials Reports, 2018, 32(2): 288 -294 .
[7] WANG Tong, BAO Yan. Advances on Functional Polyacrylate/Inorganic Nanocomposite Latex for Leather Finishing[J]. Materials Reports, 2017, 31(1): 64 -71 .
[8] WANG Wenjin, WANG Keqiang, YE Shenjie, MIAO Weijun, CHEN Zhongren. Effect of Asymmetric Block Copolymer of PI-b-PB on Phase Morphology and Properties of IR/BR Blends[J]. Materials Reports, 2017, 31(2): 96 -100 .
[9] HUANG Dajian, MA Zonghong, MA Chenyang, WANG Xinwei. Preparation and Properties of Gelatin/Chitosan Composite Films Enhanced by Chitin Nanofiber[J]. Materials Reports, 2017, 31(8): 21 -24 .
[10] WU Tao, MAO Lili, WANG Haizeng. Preparation and Defluoridation Performance of Mg/Fe-LDHO/PES Membranous Adsorbent[J]. Materials Reports, 2017, 31(14): 26 -30 .
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed