期刊论文详细信息
World Electric Vehicle Journal
Energy Consumption Prediction of Electric Vehicles Based on Digital Twin Technology
Teng Zhou1  Zhifeng Xu1  Zhaolong Zhang2  Xudong Zhang2  Yuan Zou2 
[1] Beijing Automotive Industry Corporation—Beijing Electric Vehicle (BAIC BJEV), Beijing 100176, China;Beijing Institute of Technology, Beijing 100081, China;
关键词: energy consumption;    digital twin;    electric vehicle;    modeling;   
DOI  :  10.3390/wevj12040160
来源: DOAJ
【 摘 要 】

Digital twinning technology originated in the field of aerospace. The real-time and bidirectional feature of data interaction guarantees its advantages of high accuracy, real-time performance and scalability. In this paper the digital twin technology was introduced to electric vehicle energy consumption research. First, an energy consumption model of an electric vehicle of BAIC BJEV was established, then the model was optimized and verified through the energy consumption data of the drum test. Based on the data of the vehicle real-time monitoring platform, a digital twin model was built, and it was trained and updated by daily new data. Eventually it can be used to predict and verify the data of vehicle. In this way the prediction of energy consumption of vehicles can be achieved.

【 授权许可】

Unknown   

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