Advanced Speed Control of PMSM Motor Using Neural FOC Method

Abstract

This paper investigates an artificial neural network (ANN)-based field-oriented control (NN-FOC) for a surface-mounted permanent magnet synchronous machine (SPMSM) drive. The ANN was trained by using the modified Levenberg-Marquardt MLM algorithm. The novel Maximum Torque per Ampere (MTPA) and flux weakening (FW) approach are undertaken for electric vehicle (EV) application. The proposed control is validated in simulation tests and compared with a PI based field-oriented control (PI-FOC). The simulation results show that the maximum operating speed of the proposed control is improved by 48% compared to the PI-FOC based control. Consequently the proposed neural NN-FOC controller can be a potential replacement of the existing control schemes, such as PID, fuzzy logic, or others, and provides adequate traction control in advanced electric drives, particularly in electric vehicle EV application.