Maximum Torque Per Ampere Control of Variable Flux Memory Motor Based on Online Parameter Identification

In order to achieve efficient and accurate control of variable flux memory motor (VFMM) and to address the impact of parameter changes on control performance after memory motor magnetization adjustment, a Maximum Torque per Ampere (MTPA) control method based on online parameter identification is proposed. The influence of memory motor parameter changes on the deviation of the MTPA working point is analyzed, and the MTPA control based on per-unit normalization processing is improved. Meanwhile, the rotor flux varphi and the q-axis stator inductance are identified using the forgetting factor recursive least squares (FFRLS) estimation method to ensure real-time optimal d-q-axis current distribution. Experimental results show that the error of online identification of memory motor parameters is small, the control system can effectively track the MTPA working point, effectively reducing the motor copper loss and improving the torque output capability of the memory motor after magnetization adjustment.