ANN Tuned PI Control for Solar Powered Field Oriented Control Synchronous Reluctance Motor for Electric Vehicle Applications

Electric Vehicles (EVs) are acquiring more significance because of its increased demand. Induction Motors (IMs), Synchronous Reluctance Motor (SynRM), Permanent Magnet Synchronous Motor (PMSM), Switched Reluctance Motor (SRM), and Brushless DC (BLDC) motor are most commonly used motors for EVs applications. Among these EV motors, the SynRM offers high efficiency, low maintenance, robust construction and low cost due to absence of rare earth materials. However, the main problems facing in the SynRM for EV applications with conventional speed controller has produces large overshoots, long settling time and huge steady state error during large input voltage and load variations. So as to solve these problems, Artificial Neural Network (ANN) Tuned Proportional Integral (PI) Speed Control (ANNTPISC) with Maximum Torque per Ampere Control Field Oriented Control (MTPACFOC) is designed for SynRM. The source for the SynRM is taken from solar panels with Maximum Power Point Tracking (MPPT) method. The performance of the proposed MTPACFOC based SynRM with ANNTPISC is tested at different operating conditions such as different irradiation and load variations by constructing Simulink proposed model computer simulation. Results are presents to show the proficient of the designed MTPACFOC based SynRM with ANNTPIC such as maximum efficiency of 96.20%, settling time of 0.49s, null steady state error and overshoot of 0.9% in comparison with conventional controller. Therefore, this proposed control for SynRM is most suitable for EV applications.