A comprehensive study on battery health assessment and remaining driving range estimation for electric vehicles

Huachi Xu; Jun Jia

doi:10.1117/12.3015747

6 February 2024 A comprehensive study on battery health assessment and remaining driving range estimation for electric vehicles

Huachi Xu, Jun Jia

Author Affiliations +

Proceedings Volume 12979, Ninth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2023); 1297958 (2024) https://doi.org/10.1117/12.3015747
Event: 9th International Conference on Energy Materials and Electrical Engineering (ICEMEE 2023), 2023, Guilin, China

Abstract

Electric vehicles (EVs) have emerged as a promising solution to curb greenhouse gas emissions and reduce dependency on fossil fuels. The successful integration of EVs into the mainstream transportation system relies heavily on efficient power battery utilization, making battery health assessment and remaining mileage estimation vital. This paper presents a comprehensive study on the development of intelligent energy management systems for EVs, with a primary focus on predicting battery health status and accurately estimating the remaining mileage (RDR). The study leverages cutting-edge big data analytics and machine learning techniques to enhance battery performance analysis, ensuring optimal energy utilization in electric vehicles.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Huachi Xu and Jun Jia "A comprehensive study on battery health assessment and remaining driving range estimation for electric vehicles", Proc. SPIE 12979, Ninth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2023), 1297958 (6 February 2024); https://doi.org/10.1117/12.3015747

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