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Electric vehicles are increasingly recognized as a sustainable alternative to internal combustion engine vehicles, offering significant reductions in emissions and improvements in energy efficiency. The regenerative braking system stands as a critical component in the augmentation of their performance, enabling the recuperation of kinetic energy during braking events. The present study aims to delineate the influence of braking parameters on energy recovery in electric vehicles within urban driving environments, employing a methodology that integrates real-world driving data with simulation analysis. This investigation proceeded through a dual-stage approach: initial data collection, involving sixty urban trips executed with an electric drive test vehicle, followed by simulation-based analyses utilizing the AVL Cruise software. Statistical analysis, including correlation and K-Means clustering, was employed to assess the relationship between braking parameters—such as the number of braking events, average braking speed, deceleration, and maximum braking force—and the amount of recovered energy. A significant correlation was observed between the frequency of braking events and recovered energy, with clustering analysis revealing that driving patterns characterized by frequent, moderate-intensity braking yielded the highest energy recovery efficiency. The findings indicate that frequent, moderate braking in dense urban traffic optimizes energy recovery. This investigation furnishes pragmatic insights for the development of enhanced regenerative systems and the promotion of driving methodologies that augment electric vehicle range.