Data-Driven Energy Consumption Analysis and Prediction of Real-World Electric Vehicles at Low Temperatures: A Case Study Under Dynamic Driving Cycles

Data-Driven Energy Consumption Analysis and Prediction of Real-World Electric Vehicles at Low Temperatures: A Case Study Under Dynamic Driving Cycles

Accurate analysis and prediction of low-temperature energy consumption in pure electric vehicles can provide a reliable reference for energy optimization strategies, thereby alleviating range anxiety. Here, we propose a data-driven energy consumption analysis and prediction approach for real-world e...

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Bibliographic Details
Main Authors: Yifei Zhao, Hang Liu, Jinsong Li, Hongli Liu, Bin Li
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Energies
Subjects:
electric vehicle
low temperature
energy consumption prediction
machine learning
Bayesian optimization
Online Access:https://www.mdpi.com/1996-1073/18/5/1239
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