EFFICIENCY OPTIMIZATION CONTROL METHOD AND SYSTEM FOR PERMANENT MAGNET SYNCHRONOUS MOTOR

An efficiency optimization control method and system for permanent magnet synchronous motor are provided, and the method includes: step 1: obtaining an approximate optimal direct axis (d-axis) current of a permanent magnet synchronous motor by using a loss model algorithm; step 2: performing, by using the approximate optimal d-axis current as an initial value and using a deep reinforcement learning algorithm, an optimizing process on the approximate optimal d-axis current to construct an optimal deep reinforcement learning model; and step 3: inputting currently acquired state data of the permanent magnet synchronous motor into the optimal deep reinforcement learning model to obtain a control parameter value corresponding to an optimal efficiency of the permanent magnet synchronous motor, and controlling the permanent magnet synchronous motor based on the control parameter value. Therefore, real-time target control for the permanent magnet synchronous motor is achieved.