Remaining driving range prediction for electric vehicles: Key challenges and outlook

Remaining driving range (RDR) research has continued to consistently evolve with the development of electric vehicles (EVs). Accurate RDR prediction is a promising approach to alleviate distance anxiety when power battery technology is not yet fully matured. This paper first introduces the research motivation of RDR prediction, summarizes the previous research progress, and classifies the influencing factors of RDR. Second, conduct research and analysis on the physical model of EVs, mainly including battery and vehicle models. Based on the physical model, the energy flow problem of EVs is analyzed and discussed. Third, four key challenges of RDR prediction are summarized: battery state estimation, driving behavior classification and recognition, driving condition prediction and speed prediction, and RDR calculation method. Finally, given the four challenges faced by RDR, a driving range prediction method based on vehicle-cloud collaboration is proposed, which combines the advantages of cloud computing and machine learning to provide further research trends.

Automated summary

This paper introduces the research motivation, progress, and influencing factors classification of remaining driving range (RDR) prediction. It conducts research and analysis on the physical model of electric vehicles (EVs) and discusses the energy flow problem. Four key challenges of RDR prediction are summarized, and a driving range prediction method based on vehicle-cloud collaboration is proposed.