Perpustakaan Digital ITB

Regenerative braking is a key technology in electric vehicles (EVs) that improves energy efficiency by converting kinetic energy during braking into electrical energy for battery recharging. However, the efficiency of regenerative braking varies depending on driving conditions. This thesis aims to evaluate the regenerative braking efficiency of an EV under controlled and real-world driving conditions by analysing the amount of energy recovered during braking sections. A simplified EV model obtained from MATLAB File Exchange, originally developed by Nural Mammadov for Simulink, was used and adapted accordingly to the specifications of a Hyundai IONIQ 5. Two types of drive cycles were investigated, namely controlled drive cycles with varying constant deceleration rates and GPS-derived drive cycles collected using a smartphone application, RaceChrono, during real world driving. The driving data were processed using Microsoft Excel before being implemented into the Simulink model. Regenerative braking sections were identified based on the motor torque output. Furthermore, kinetic energy loss, recovered electrical energy, and regenerative braking system (RBS) efficiency were calculated as the main outputs. The results show that regenerative braking efficiency varies significantly with driving conditions. The controlled drive cycles in the form of constant deceleration rates established a baseline where the highest RBS efficiency achieved was 56.19%, while the GPS-derived drive cycles showcased a greater variability due to the realistic driving behaviour. Thus, no clear trend was found between initial braking speed and RBS efficiency. However, the simulations showed RBS efficiency falls to near zero below the speed of around 25 km/h.