Real-Time Multi-Parameter estimation Based Loss Minimization Control for IPMSM

To address the increased solving errors and low operating efficiency caused by variations in parameters such as inductance and flux linkage in the traditional loss minimization control (LMC) methods for interior permanent magnet synchronous motor (IPMSM), a real-time multi-parameter-based LMC for IPMSM is proposed in this paper. Firstly, based on the mathematical model of IPMSM considering iron losses, a Lagrange function is constructed to set the d-q-axis current reference values under the premise of meeting the optimal efficiency. Furthermore, based on the compensation of inverter nonlinear voltage error, the motor parameters include d-q-axis inductance, stator resistance, permanent magnet flux and iron loss resistance are estimated online to reduce the impact of parameter mismatch. The proposed method not only avoids the complex calculation of higher order nonlinear equations but also reduces the impact of motor parameter mismatches on the accuracy of the LMC, thereby effectively enhancing motor operation efficiency. Experimental results demonstrate that the proposed method achieves significant efficiency optimization under various operating conditions. Compared to the maximum torque per ampere (MTPA) control and the approximate LMC method, the proposed method achieves maximum efficiency improvements of 1.19% and 0.38%, respectively.