Research On New Method Of Parameter Identification Of Permanent Magnet Synchronous Motor

Permanent magnet synchronous motor(PMSM)has the advantages such as high efficiency,low rotor inertia,low losses and energy conservation,etc.It has been widely used in new energy wind power generation,aerospace,high speed train,numerical control machine,flexible manufacturing and other high performance servo control field.At present,the relevant parameters of PMSM are required to be used in the design of the controller and fault diagnosis.In order to ensure the safe and reliable operation of motor,takeing PMSM as the research object in this paper,new PMSM parameter identification methods are proposed.The parameter identification of permanent magnet synchronous motor based on improved cuckoo algorithm is designed.Cuckoo search algorithm has the advantages such as simple,less parameters,faster convergence rate etc.,but it also has the defects of premature convergence and low computational accuracy.In view of the deficiency of cuckoo search algorithm,designing the fuzzy reasoning based on the degree of cloud membership to adjust the probability of an alien egg discovered by host nests and using adaptive variable step method to adjust step size of Lévy flights.The improved algorithm can improve identification precision and optimization ability.Permanent magnet synchronous motor multi-parameter identification results show that improved cuckoo algorithm can effectively identify the motor parameters.Health condition monitoring problem of permanent magnet synchronous motor can be treated as a multi parameter identification problem of permanent magnet synchronous motor.In order to improve the efficiency of PMSM health status monitoring,a kind of health condition monitoring method of permanent magnet synchronous motor is designed based on multi-agent bat algorithm.The competition and cooperation operation of multi-agent enhances the communication of agents,and improve the ability of global optimization and the dynamic tracking performance of the algorithm.Self-study operation can improve local search ability and convergence rate of the algorithm.The multi-parameter identification results of permanent magnet synchronous motor show that multi-agent bat algorithm can quickly and efficiently identify the parameters of motor.The task of monitoring and early warning can be implemented for the running permanent magnet synchronous machine according to the changed parameters.In view of the chaotic running state in the permanent magnet synchronous motor,a kind of parameter identification method of permanent magnet synchronous motor chaotic system is designed based on Hamiltonian adaptive state observer.The mathematical model of permanent magnet synchronous motor can be converted into a classic Lorenz chaotic model through a series of state transformation,and within certain parameters,the motor emerges chaotic phenomenon.Constructed the port controlled Hamiltonian system model of the chaotic systems,and the thought "expansion + feedback" been used,the port controlled Hamiltonian adaptive state observer is designed,and parameter identification can be completed in the process of state observation.Hamiltonian model can make full use of the physical structure of system itself,and the structure of state observer designed is simple,easy to implement.It can observe the internal structure and information of the system.Simulation shows the effectiveness of the adaptive observer,and the high precision identification is realized.