Comprehensive Framework for Energy Consumption Estimation in Electric Vehicles

Accurately predicting the energy consumption of Battery Electric Vehicles (BEVs) is essential for addressing range anxiety, optimizing route planning, and governing infrastructure investments in a rapidly electrifying transportation sector. This paper presents a generalized, flexible, and probably the most comprehensive modeling framework designed to estimate BEV energy consumption under different driving conditions, vehicle configurations, and environmental influences. The model is structured in mechanical, electrical, and auxiliary sub-models. The model incorporates detailed input parameters, such as aerodynamic coefficients, transmission and motor characteristics, regenerative braking constraints, battery capacity, climate control demands, and ambient conditions. Validation results demonstrate a strong alignment between measured and predicted power profiles, with a high coefficient of determination, low RMSE, and low MAE confirming the model’s reliability and adaptability. The introduced framework can be extended to various BEV segments, driving cycles, and environmental conditions, providing valuable information for vehicle manufacturers, fleet managers, and policymakers aiming to improve EV performance, route efficiency, and charging infrastructure deployment.