MATLAB-Based analysis of energy recovery performance of regenerative braking systems under different driving conditions in electric vehicles

The limited battery capacity of electric vehicles has made the development of effective energy management strategies essential for improving energy efficiency and extending driving range. Regenerative braking systems contribute to this objective by converting the vehicle's kinetic energy during braking into electrical energy and storing it in the battery. In this study, the effects of different driving conditions on regenerative braking performance were comparatively investigated using a unified MATLAB-based computational model applied to four different electric vehicle segments. Four vehicle models, namely Small EV, Sedan EV, SUV EV, and Large SUV, were evaluated under four representative driving scenarios: urban, intercity, highway, and hilly-road driving. The model was used to calculate energy recovery efficiency, recovered energy, net energy consumption, specific energy consumption, and battery utilization ratio. The results showed that the energy recovery efficiency reached approximately 20% under urban driving conditions, whereas it decreased to approximately 3% during highway driving. Although an increase in vehicle mass resulted in a higher amount of recovered energy, it also led to greater overall energy consumption. The observed variations across driving scenarios were generally greater than the differences among vehicle segments. The main contribution of this study is the comprehensive evaluation of energy management performance by comparing different electric vehicle segments under identical computational and driving conditions. Furthermore, the proposed MATLAB-based computational model provides a practical and systematic framework for comparatively evaluating regenerative braking and energy management performance under different vehicle and driving conditions.