Optimizing Regenerative Braking in Electric Vehicle: A Comprehensive Study of Control Strategies and Energy Recovery

This study investigates the concept of regenerative braking in electric vehicles (EVs) and electric multiple units (EMUs), focusing on simulation and hardware in the loop (HIL) testing. This study analyses the power variation between non regenerative and regenerative braking modes, emphasizing the optimization of energy recovery and efficient power distribution. A two-stage control strategy that integrates field-oriented control for speed regulation and a DCDC converter for managing power between a battery and an ultracapacitor in a hybrid energy storage system (HESS) is proposed. The proposed system was validated through MATLAB simulations and HIL experiments, which demonstrated enhanced energy recovery, efficient load balancing, and improved battery protection. In addition, this study introduces a Mamdani fuzzy inference system for optimizing regenerative braking in fuel cell buses, considering safety, driving dynamics, and occupant comforts. The design of robust H∞ controllers further ensure system stability and minimizes disturbances during regenerative braking. The experimental results show that the H∞ controller outperforms traditional PI controllers in terms of energy recovery and dynamic response under various driving conditions. This study contributes to the advancement of regenerative braking technologies, offering insights into power system stabilization and energy conservation for both EVs and EMUs.