Abstract: Aiming at the problems of slow identification speed and large identification error in parameter identification of permanent magnet synchronous motor (PMSM), an improved walrus optimization algorithm (IWaOA) is proposed for parameter identification. The Circle chaotic mapping is used to generate the whale population to improve the quality of the initial solution. The concept of pheromones in the black widow algorithm was introduced in the foraging stage of walruses to improve the global optimization ability of the algorithm, A triangular walking strategy integrating the outlier boundary and greedy rule is employed to search the area where the leader of the walrus population is located, thereby enhancing the local exploration ability of the algorithm. A permanent magnet synchronous motor model is established and the IWaOA algorithm is used to identify the stator resistance, d-q axis inductance, and permanent magnet flux linkage of the motor. Simulation results show that the identification errors of the four parameters by the IWaOA algorithm are all within 0.2%, with the minimum identification error being less than 0.02%, which proves the effectiveness and reliability of the proposed algorithm for parameter identification of permanent magnet synchronous motors.