大数据分析技术在新能源汽车行业的应用综述——基于新能源汽车运行大数据

doi:10.3901/JME.2019.20.003

摘要/Abstract

摘要： 为应对化石能源危机和环境污染问题，新能源汽车技术的发展与应用引起广泛重视。新能源汽车具有高信息化的特点和智能网联化的发展趋势，在日常运行中会产生大量行驶数据信息。利用海量多源异构数据进行安全预警与监管、车辆技术分析，是推动我国新能源汽车行业发展的关键。综述了大数据分析技术在新能源汽车行业的应用情况，概述了大数据分析技术的基础理论、发展历程，介绍了新能源汽车国家监测与管理平台的架构和功能，并着重阐述了新能源汽车大数据分析过程。分别从动力电池数据、汽车运行数据和充电数据的角度出发，分析了现有的研究方向和研究方法，列举了部分研究成果和应用情况。最后，对当前新能源汽车大数据分析领域存在的问题和发展应用前景进行了总结和展望。

关键词: 新能源汽车, 大数据平台, 大数据分析方法, 动力蓄电池

Abstract: New energy vehicle(NEV) has been widely used around the world in response to the fossil energy crisis and environmental pollution problems. NEV will generate massive real-world data during its daily operating which is contributed by high electrification and intelligent networking. Applying these multi-source heterogeneous data for a security warning and technical analysis will play a key role in promoting the development of NEV industry in China. The current situation of data-driven analysis technology in the NEV field is reviewed. Firstly, the basic theory of big data analysis techniques are introduced and the development of big data technology is depicted. The structure and function of the National Monitoring and Management Platform for New Energy Vehicles are introduced, and the particular process of big data analysis on NEV is emphasized. The previous data-driven research and methods in power battery, NEV daily operation and charging behavior are proposed for discussion respectively. Some representative research results and applications are displayed at the same time. Finally, the issues and prospects of the data-driven method on NEV application field are summarized and forecasted.

Key words: new energy vehicle, big data platform, data-driven methods, power battery

中图分类号:

U469

佘承其, 张照生, 刘鹏, 孙逢春. 大数据分析技术在新能源汽车行业的应用综述——基于新能源汽车运行大数据[J]. 机械工程学报, 2019, 55(20): 3-16.

SHE Chengqi, ZHANG Zhaosheng, LIU Peng, SUN Fengchun. Overview of the Application of Big Data Analysis Technology in New Energy Vehicle Industry: Based on Operating Big Data of New Energy Vehicle[J]. Journal of Mechanical Engineering, 2019, 55(20): 3-16.

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