Improved MTPA Control Strategy with Adaptive Gain for Permanent Magnet Synchronous Reluctance Motors

Maximum torque per ampere control (MTPA) is widely employed in interior permanent magnet synchronous reluctance machine (IPMSynRM) control to minimize copper losses during motor operation. However, the traditional MTPA control methods have limited capability to consider the variation of motor parameters due to magnetic saturation and the convergence algorithm is relatively simple, which leads to control errors under heavy loads and poor dynamic performance under light loads. Thus, this paper combines the parameter identification algorithm to include the inductance variation into the MTPA control formula when the operating conditions change. Also, the gradient descent algorithm is employed to introduce the adaptive gain to optimize the convergence algorithm. The accuracy of MTPA operating point and dynamic performance are improved in a wide load range.