Energy Consumption Prediction of Electric Vehicles Based on Digital Twin Technology

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.

Automated summary

Digital twinning technology, originating in aerospace, offers high accuracy, real-time performance, and scalability through real-time bidirectional data interaction. This study introduces digital twin technology to electric vehicle energy consumption research, establishing and optimizing a consumption model to predict vehicle energy consumption.