Enhancing regenerative braking efficiency in electric vehicles through urban driving pattern analysis

Electric vehicles offer a sustainable alternative to internal combustion engine vehicles, significantly reducing emissions and improving energy efficiency. A key feature is the regenerative braking system, which recovers kinetic energy during braking. This study examines how braking parameters affect energy recovery in EVs under urban conditions, combining real-world data with simulation. The research involved two stages: data collection from 60 urban trips using a Hyundai Kona Electric, followed by AVL Cruise simulations. Statistical analysis (correlation and K-Means clustering) assessed the relationship between braking parameters (number of events, average braking speed, deceleration, maximum braking force) and recovered energy. Results showed a strong correlation (r = 0.9) between the number of braking events and recovered energy, highlighting the importance of frequent urban braking. Clustering identified four driving patterns. Cluster C4, with the highest number of braking events (84–158) and moderate intensity, achieved the greatest energy recovery efficiency (23.16%). Cluster C1, with fewer events (26–76) and smoother driving, showed the lowest efficiency (18.45%). The average efficiency across all trips was 21.47%, consistent with the literature. Findings suggest that frequent, moderate braking in dense urban traffic optimizes energy recovery. The study offers practical insights for designing more efficient regenerative systems and promoting driving techniques that enhance EV range.