Impact of Weather Conditions on Energy Consumption Modeling for Electric Vehicles: A Data-Driven Analysis

This study presents a methodology to develop 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 energy consumption modeling. To improve model accuracy, temperature and vehicle acceleration data were clustered using the K-Means method. As a result, four energy consumption models were created, each corresponding to a specific data cluster. This approach achieved strong validation results, with an R² value of 0.84 and a MAE ranging from 0.75 to 1.23 Wh, which is a satisfactory outcome given the large volume of input data. These models are designed for microscale energy consumption prediction, using vehicle speed and acceleration as input parameters.