Loss Minimization Control of SPMSM Based on Virtual Signal Injection

The key to optimizing the efficiency of Permanent Magnet Synchronous Motors (PMSMs) lies in how to obtain accurate and stable loss minimization criteria without solving complex loss equations. This paper first compensates for inverter nonlinear voltage error and estimates motor parameters including iron loss resistance, d-q-axis inductance, and permanent magnet flux linkage, thereby reducing the impact of parameter variations on loss power estimation. Then takes the id as the signal injection target, uses the difference in motor loss before and after signal injection as the loss minimization control (LMC) criterion, and proposes an LMC method for Surface Permanent Magnet Synchronous Motor (SPMSM). The LMC criterion of the proposed method is accurate and stable, which avoids solving complex loss models and reduces the computational burden. Experimental results show that the proposed method can improve motor efficiency under different operating conditions by up to 1.32% compared to the Maximum Torque Per Ampere (MTPA) control method.