An Integrated Parameter Identification Method of Asynchronous Motor Combined with Adaptive Load Characteristics

The existing asynchronous motor parameter identification methods only identify the parameters of the asynchronous motor itself, ignoring the identification of the parameters of the load carried by the asynchronous motor. This paper proposes an integrated parameter identification method of the asynchronous motor that uses the improved PSO (Particle Swarm Optimization, PSO) and considers the load adaptive characteristics. Compared with the traditional method, this method firstly combines the PSO method with Space Disturbance (SD) to form an improved PSO method, which prevents the PSO from falling into a local optimal state and enhances the global optimization ability of the PSO method. Secondly, according to the characteristics of different loads, a load identification strategy is constructed. This strategy can judge the type of load carried by the asynchronous motor, which reduces the optimization exploration space of the PSO algorithm and accelerates the optimization speed of the PSO algorithm. Finally, according to the identified load types, the improved particle swarm optimization algorithm combined with the spatial disturbance is used to realize the integrated identification of the asynchronous motor and the load parameters. The validity of the algorithm is verified by an example, and the factors affecting the identification accuracy are analyzed.