Chinese researchers have developed a novel data-driven framework for real-time estimation and analysis of the remaining driving range of electric vehicles (EVs), addressing one of the key challenges for EV drivers: range anxiety, according to Chinese media.
Despite the growing presence of eco-friendly EVs on roads, accurately predicting the remaining driving range remains difficult due to the coupling effects of driving behavior, ambient temperature, and battery aging.
To overcome these challenges, researchers from the Dalian Institute of Chemical Physics (DICP), Chinese Academy of Sciences, devised a method for calculating energy consumption and battery state of health based on real vehicle operation data, according to a research article published in Applied Energy.
The team developed a per-mile energy consumption model by integrating multiple factors, including driving behavior, ambient temperature, and battery health, enabling precise prediction of the remaining range. This staged approach also identifies which factors contribute most to driving range.
The framework was validated on passenger vehicles and buses across several domestic cities over a three-year period. Using real operational data covering over 300,000 kilometers, the model achieved a mean relative error of less than 5.5 percent in range prediction.
Researchers noted that by adjusting driving behavior, the driving range can be improved by over 30 percent for passenger vehicles and over 10 percent for buses.
The framework is expected to support smart fleet dispatch, energy-optimal operations, and residual-value appraisal of EVs. Future research will expand its applicability to colder regions and more complex road conditions, incorporating additional environmental parameters such as road surface and humidity.
The study will also focus on integration with on-board battery management systems and cloud-based platforms to enhance the safety and efficiency of new-energy transportation systems, according to DICP.