Braking control strategies based on single-pedal regenerative braking and neural network for Electric Vehicles

Braking systems and braking control strategies play a vital role in improving the overall vehicle performance like vehicle and passenger safety, overall vehicle efficiency, vehicle stability, and much more. Braking control strategies based on single-pedal regenerative braking and neural network for electric vehicles will ensure braking stability as well as improvement in overall vehicle energy economy to reduce the driver range anxiety to some extent. To better utilize the regenerative braking potential of the motor, to improvise the overall energy recovery characteristic of the vehicle, and to reduce the driving difficulties of the user, the fuzzy logic-controlled algorithm is implemented on a single pedal accelerator electric vehicle. Driving characteristics and driver’s intentions can be identified through pedal operations. Releasing the single pedal (acceleration pedal) and Stepping on the brake pedal is the two-braking process of the driver. A single-pedal-based regenerative braking control approach (RBC) is designed to facilitate proper regeneration brake torque to the motor to fulfill the braking needs from the driver all the time, in the first braking process. A neural network-based controller is proposed for the emergency braking operation to optimize the braking stability as well as the energy, in the second braking process.