Enhancing Regenerative Braking Efficiency in Electric Vehicles: An Advanced Fuzzy Logic-Based Control Strategy

The level of interest in electric vehicle technology innovation has surpassed all expectations. This paper investigates the fundamental structure and advancement of regenerative braking technology. Unlike traditional hydraulic braking methods, which waste a significant amount of energy by producing excess heat, regenerative braking technology not only reduces heat production but also incorporates electrical power into the system. As a result, regenerative braking technology not only mitigates the disadvantages of traditional methods, but it also saves energy for high-efficiency applications. In the regenerative mode that follows, the motor acts as a generator, converting mechanical energy into electrical power. The brake controller monitors throttle release and wheel speed to determine the optimal PWM pulse for regeneration. Advanced control algorithms such as fuzzy logic, PID controllers, and the integration of an anti-lock braking system can be used to improve the controller. Furthermore, the incorporation of advanced energy storage systems such as flywheels and supercapacitors has the potential to significantly improve regeneration. Finally, machine learning techniques such as neural networks can be used to improve the power distribution balance between the battery, supercapacitor, and motor. The driving range of an electric vehicle can be increased by 8–25 % by incorporating regenerative braking.