The accurate identification of the equivalent circuit parameters of the asynchronous motor played an important role in motor control. At the same time, the variation of the equivalent circuit parameters could reflect the running state of the motor, so the parameter identification was also applied to the motor fault diagnosis. The modern optimization algorithm was applied to the equivalent circuit parameter identification of threephase asynchronous motor. By combining particle swarm optimization PSO algorithm with simulated annealing (SA) algorithm, six equivalent parameters of asynchronous motor could be identified accurately and effectively. Compared with genetic algorithm, the proposed algorithm was easier to implement and converged more rapidly. The algorithm was implemented by using the model in dqcoordinate system of asynchronous motor considering iron loss. Taking into account the influence of temperature on the resistance parameters, the algorithm was proved to be effective in identifying the motor parameters and tracking resistance changes through examples.