Vector Control in Permanent Magnet Synchronous Reluctance Generator Using a BSR Hybrid Optimization

Special electric machines have specific designs to improve efficiency and the PMSRG drives are mostly attracted by their characteristics of low-cost, high-power density and efficiency. Vehicle mechanical structure of the machine is improved by the technology and the Permanent Magnet synchronous Machine (PMSRG) machines operate with electrical and magnetic circuits in the rotor structure. The rotor of the machine acts as a cog-induced machine based on the machine design and the machine initially moves the induction stage and then enters the synchronous area by the reluctance torque. Energy conservation of a machine plays a vital role in the machines and the power losses, and harmonics distortion are considered. In this research, the magnetic saturation effect is considered by the optimized controller and the maximum torque was obtained by the Maximum Torque per Ampere (MTPA) strategy. An optimized control strategy based on the learning system provides the results for the control process of flux and speed. Vector control (VC) of PMSRG is compared with the various controllers. Additionally, the PI controller is optimized by using brainstorm and search and rescue optimization. The proposed BSR hybrid optimized controller attains the values of field voltage, stator dq voltage and phase modulation waveform are 228.28 V, 9.78 and 0.98 V. The Performance of the model is implemented in MATLAB to perform different Performance Metrics for the Performance Evaluation.