MODELING, SIMULATION, AND FUZZY LOGIC BASED DESIGN AND PERFORMANCE EVALUATION OF A REGENERATIVE BRAKING SYSTEM FOR A CONVERTED 1987 TOYOTA COROLLA ELECTRIC VEHICLE USING MATLAB/SIMULINK

Abstract

The increasing adoption of electric vehicles has intensified the need for efficiency improvements, particularly in converted electric vehicles constrained by limited battery capacity. Although regenerative braking (RB) is a well-established energy recovery technique, its integration in small scale vehicle conversions remains limited, and existing implementations often lack optimized control strategies, realistic drive-cycle validation, and comprehensive system-level modeling, leaving critical performance gaps unresolved. This study addresses these challenges through the simulation-based modeling, design, and analysis of a regenerative braking system for a converted 1987 Toyota Corolla electric vehicle, evaluated under the FTP-75 driving cycle. A detailed vehicle and powertrain model was developed in MATLAB/Simulink, incorporating the battery system, electric motor, drivetrain, and a fuzzy logic–based control algorithm designed to dynamically regulate regenerative braking torque under varying operating conditions. The system was evaluated under two scenarios with and without regenerative braking while maintaining an initial battery state of charge (SOC) of 70% to ensure safe charging limits. Simulation results demonstrate that the proposed control strategy effectively enhances energy recovery during frequent stop-and-go urban conditions, increasing the final SOC from 61.79% without RB to 63.04% with RB. This improvement corresponds to a 18% increase in energy efficiency and an extension of driving range by 39.5 km. These results indicate that a properly designed and controlled regenerative braking system can improve energy utilization and driving range in converted electric vehicles, highlighting the potential of fuzzy logic–based control for managing nonlinear braking dynamics.