Impact of Weather Conditions on Energy Consumption Modeling for Electric Vehicles

Maksymilian Mądziel ()
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Maksymilian Mądziel: Faculty of Mechanical Engineering and Aeronautics, Rzeszow University of Technology, 35-959 Rzeszow, Poland

Energies, 2025, vol. 18, issue 8, 1-21

Abstract: This study presents a methodology for developing an energy consumption model for electric vehicles based on dynamic vehicle and environmental data. Particular attention is given to analyzing the impact of ambient temperature on the energy consumption modeling. The approach leverages a large dataset to enhance model robustness while acknowledging the constraints imposed by the selected explanatory variables—vehicle speed and acceleration. To improve the model’s accuracy, temperature and acceleration data were clustered using the K-Means method, resulting in four distinct energy consumption models tailored to specific data clusters. Despite the inherent limitations of using only speed and acceleration as predictors, the proposed models achieved strong validation results, with an R 2 value of 0.84 and a MAE ranging from 0.75 to 1.23 Wh. This approach enables microscale energy consumption prediction while ensuring broad applicability across various driving scenarios.

Keywords: electric vehicle; modeling; energy consumption; machine learning (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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