基于电池荷电状态和行驶工况辨识的电动汽车续驶里程估算
详细信息    查看全文 | 推荐本文 |
  • 英文篇名:Driving Range Estimation for Electric Vehicles Based on Battery SOC and Driving Cycle Identification
  • 作者:连静 ; 郑宁安 ; 周雅夫 ; 李琳辉 ; 麻笑艺 ; 王翰涛
  • 英文作者:LIAN Jing;ZHENG Ning-an;ZHOU Ya-fu;LI Lin-hui;MA Xiao-yi;WANG Han-tao;School of Automotive Engineering,Faculty of Vehicle Engineering and Mechanics,State Key Laboratory of Structural Analysis for Industrial Equipment,Dalian University of Technology;
  • 关键词:纯电动汽车 ; 续驶里程 ; 城市交通 ; 模糊C聚类分析
  • 英文关键词:electric vehicle;;driving range;;urban traffic;;fuzzy C-means clustering
  • 中文刊名:KXJS
  • 英文刊名:Science Technology and Engineering
  • 机构:大连理工大学工业装备结构分析国家重点实验室运载工程与力学学部汽车工程学院;
  • 出版日期:2016-05-08
  • 出版单位:科学技术与工程
  • 年:2016
  • 期:v.16;No.374
  • 基金:国家自然科学基金(61203171,61473057);; 中国博士后科学基金(2012M510799,2013T60278);; 中央高校基本科研业务费专项基金(DUT15LK13)资助
  • 语种:中文;
  • 页:KXJS201613020
  • 页数:5
  • CN:13
  • ISSN:11-4688/T
  • 分类号:118-122
摘要
为消除驾驶员因电动汽车续驶里程估计不准确,产生的"里程焦虑"。提出了一种基于电池荷电状态和行驶工况辨识的电动汽车续驶里程估算模型。以大连市某电动汽车运行数据为研究对象,首先分析了SOC与行驶里程的相关性,将工况数据划分为432个工况片段。然后利用主成分分析、模糊C聚类分析对工况片段进行分类、辨识,并建立了续驶里程的估算模型,进行续驶里程的估算。最后利用实车数据,在Matlab中进行仿真验证,结果表明此方法是可行的,所建立的模型具有较高的准确度。
        To reduce driver's range anxiety,caused by imprecise range estimation. An estimation method was proposed,which based on battery SOC and driving cycle identification. All the data is collecting from electric vehicles running in Dalian. Firstly after calculate the correlation between SOC and driving range,the data is divided into 432 segments,then segments is clustered and identified by principal Component analysis method and fuzzy cluster analysis method,and an estimation model is established. Finally an experimental using practical data is test in matlab,result confirm that the estimation method is feasible,and the estimation model has decent accuracy.
引文
1 Neubauer J,Brooker A,Wood E.Sensitivity of battery electric vehicle economics to drive patterns,vehicle range,and charge strategies.Journal of Power Sources,2012;209:269—277
    2 陈清泉,孙逢光,祝嘉光.现代电动汽车技术.北京:北京理工大学出版社,2004:15—28Chen Q Q,Sun F G,Zhu J G.Modern electric vehicle technology.Beijing:Beijing Institute of Technology Press,2004:15—28
    3 Cunningham I,Burnham K.Online use of the fuzzy transform in the estimation of electric vehicle range.Measurement and Control,2013;46 (9):277—282
    4 陈勇,孙逢春.电动汽车续驶里程及其影响因素的研究.北京理工大学学报,2001;21:(5):574—578Chen Y,Sun F C.Study on range and its related factors of electric vehicles.Journal of Beijing Institute of Technology,2001;21:(5):578 —582
    5 尹安东,赵韩,周斌,等.基于行驶工况识别的纯电动汽车续驶里程估算.汽车工程,2014;36:(11):1310—1315Yin A D,Zhao H,Zhou B,et al.Driving range estimation for battery electric vehicles based on driving cycle identification.Automobile Engineering,2014;36:(11):1310—1315
    6 毕军,张家玮,张栋,等.电动汽车行驶里程与电池soc相关性分析与建模.交通运输系统工程与信息,2015;15:(1):49 —54Bi J,Zhang J W,Zhang D,et al.A correlation analysis and modeling for battery SOC and driving mileage of electric vehicle.Journal of Transportation Systems Engineering and Information Technology,2015;15:(1):49—54
    7 时立文.SPSS 19.0统计分析从入门到精通.北京:清华大学出版社,2012:149—165Shi L W.SPSS 19.0 statistical analysis from entry to the master.Beijing:Tsinghua University Press,2012:149—165
    8 何晓群.多元统计分析.北京:中国人民大学出版社,2012:152 —206He X Q.Multivariate statistical analysis.Beijing:Renmin University Press,2012:152—206
    9 石琴,仇多洋,吴靖.基于主成分分析和FCM聚类的行驶工况研究.环境科学研究,2012;25:(1):70—76Shi Q,Qiu D Y,Wu J.Study on driving cycles based on principal component analysis and fuzzy C-Means clustering.Research of Environmental Sciences,2012;25:(1):70—76
    10 Montazeri-Gh M,Fotouhi A,Naderpour A.Driving patterns clustering based on driving features analysis.Journal of Mechanical Engineering Science,2011;225(6):1301—1317

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700