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

Translated title of the contribution: Overview of the Application of Big Data Analysis Technology in New Energy Vehicle Industry:Based on Operating Big Data of New Energy Vehicle

Research output: Contribution to journalReview articlepeer-review

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.

Translated title of the contributionOverview of the Application of Big Data Analysis Technology in New Energy Vehicle Industry:Based on Operating Big Data of New Energy Vehicle
Original languageChinese (Traditional)
Pages (from-to)3-16
Number of pages14
JournalJixie Gongcheng Xuebao/Chinese Journal of Mechanical Engineering
Volume55
Issue number20
DOIs
Publication statusPublished - 20 Oct 2019

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production

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