Performance Enhancement based Artificial Intelligence of Electric Vehicle under System Uncertainties

Electric vehicles (EVs) are often considered as an environmental alternative compared with conventional internal combustion engines vehicles (ICEVs). So, it is essential to explore the energy consumption behavior of EV under different conditions, in order to accurate analysis for electric vehicles. The variation of power consumption for EVs under different weather conditions is studied while implementing different driving conditions. Artificial intelligence algorithm is used to identify proportional-integral (PI) controller to improve speed control, reduce steady state error, adapt to load changes and enhance energy efficiency. Transient search optimization technique is applied to get the optimal values for PI controller gains. The system is constructed and validated using Matlab/Simulink. The obtained results show the impact of the different conditions on torque, speed and power consumption of EV. It is noticed that the positive values of incline effect on speed where the speed decreased from 53 mph to 45 mph, torque increased from 10 N.m to 90 N.m and power consumption increased from 15 kW to 38 kW. Whereas the negative values of incline effect on motor where the motor in this case was acted as generator and charge the battery where the state of charged increased from 0.64 to 0.66. The power of wind effects on the motor temperature where increased from 39 °C to 68 °C and effects on torque also where distortion is occurred on torque. The environment temperature effects on the motor temperature where motor temperature increased from 54 °C to 58 °C.