Estimation of Regenerative Braking Force in Electric Vehicles for Maximum Energy Recovery

The drive range of the Electric vehicle is limited and is dependent on the energy stored in the battery/supercapacitor. In order to enhance, the force during regeneration has to be maximized within the braking time available and has been achieved by estimating the force using fuzzy based logic and artificial neural networks to put forth the estimator with maximum energy recovery. To ensure the safety of the vehicle, all the four wheels has to be locked simultaneously which is achieved by the braking force distribution curve. An algorithm has been implemented in MATLAB/Simulink to distribute the front braking force between the regenerative and frictional brakes. With the artificial neural network, there has been an 8.33% increase in the power extracted compared to that of the fuzzy logic controller and driving range has been increased by 25.7% compared to the non-regenerative braking condition.