交通运输系统工程与信息

交通运输系统工程与信息 ›› 2015, Vol. 15 ›› Issue (1): 49-54.

• 智能交通系统与信息技术 • 上一篇    下一篇

电动汽车行驶里程与电池SOC 相关性分析与建模

毕军*1，张家玮1，张栋1，程勇2   

  1. 1. 北京交通大学城市交通复杂系统理论与技术教育部重点实验室，北京100044； 2. 济宁市鸿翔公路勘察设计研究院，山东济宁272000
  • 收稿日期:2014-06-30 修回日期:2014-08-22 出版日期:2015-02-25 发布日期:2016-02-25
  • 作者简介:毕军（1973-），男，山东济宁人，教授.
  • 基金资助:

    中央高校基本科研业务费专项资金(2013JBM052)；北京市科技计划项目（Z111109073511001).

A Correlation Analysis and Modeling for Battery SOC and Driving Mileage of Electric Vehicle

BI Jun1, ZHANG Jia-wei1, ZHANG Dong1，CHENG Yong2   

  1. 1. MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, China; 2. Jining Hongxiang Highway Survey Design and Research Institute, Jining 272000, Shandong，China
  • Received:2014-06-30 Revised:2014-08-22 Online:2015-02-25 Published:2016-02-25

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被引次数

16

摘要：

为解决电动汽车驾驶员里程焦虑问题，并为车辆行驶里程预测提供重要依据，本文提出一种基于数据驱动的方法来探讨电动汽车行驶里程和电池SOC之间的关系.首先对采集的原始数据进行删除、插值和平均处理，再对电动汽车行驶里程和电池SOC进行相关性分析并建立模型，利用递推最小二乘法对模型参数进行辨识.利用北京市运营物流电动车的数据对建立的模型及参数辨识结果进行验证.实验结果表明，本文采用的基于数据驱动预测行驶里程的方法是可行的，所建立的行驶里程与电池SOC模型具有较高的准确度.

关键词: 城市交通, 行驶里程预测, 数据驱动, 电动汽车, 电池SOC

Abstract:

In order to solve range anxiety problems of the electric-vehicle drivers, and provide an important basis for the prediction of driving mileage. This paper proposes a method based on data driving to explore the relationship between the electric car driving mileage and battery SOC(State of Charge). Firstly, original data are processed by deleting, interpolation and averaging methods. The correlation is analyzed between driving mileage and battery SOC, and the model is established. Recursive least-squares method is studied to identify the parameters. Moreover, all experiments are performed by using the practical data from pure electric logistics vehicles running in Beijing to verify the established model and parameters identification result. The experimental results confirm that the prediction method of driving mileage based on data driving is feasible, and the model between driving mileage and SOC is established with high accuracy.

Key words: urban traffic, prediction of driving mileage, data driving, electric vehicle, battery SOC

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