Efficiency Optimization Of Induction Motor Based On Parameter Identification

Asynchronous motor because of its low cost,simple and reliable,widely used in the fan pump load drag,vector control makes the performance of asynchronous motor has been further improved,so that it expands to more high-performance drive fields,become the absolute main force in the field of industrial electricity.But in many applications,asynchronous motors work for a long time in the no-load or light-load state,then the motor efficiency is greatly reduced.In order to solve this problem,some industrial frequency converter has been set up according to the actual working condition(less than full load)of the magnetic flux set values,to improve the efficiency of induction motor,but the weak magnetic flux is usually calculated according to the theory of the motor parameters,operation in the process of motor parameters change,there is room to further improve the efficiency of the motor and now.Aiming at the above problems,this paper proposes an efficient optimization algorithm for motor parameter identification of asynchronous motor,and verifies the parameter identification algorithm and efficiency optimization algorithm of asynchronous motor through simulation and experiment.The main work of this paper is as follows:First,the research progress of efficiency optimization control and parameter identification is summarized and analyzed.The cause of loss of induction motor is analyzed,and the influencing factors of loss of induction motor are defined.Second,in view of the complex structure and high order of the current three-phase motor mathematical model considering iron loss,which is not convenient for subsequent simulation research,a six-order mathematical model of induction motor considering iron loss is derived.Thirdly,the rotor flux calculation formula considering iron loss is derived,and the control system is simulated and analyzed in the Matlab/Simulink environment.The principle of efficiency optimization based on the loss model method is analyzed,and the given expression of minimum and the efficiency optimization algorithm based on optimal flux control is designed.Fourthly,a parameter identification method based on Model Reference Adaptive is proposed to solve the problems of large computation amount,difficult implementation,easy to be interfered by environmental factors and low identification accuracy of traditional identification algorithm.The method is simple to implement and does not need complex iteration and calculation process.The calculation process is robust and the calculation accuracy is high.The system is simulated and verified in Matlab/Simulink environment,and the error of the identification result is less than 0.5%.The validity and feasibility of the proposed online identification method are proved.At the same time,in view of the problem that the PI controller parameters of the adaptive rate are difficult to adjust in the MRAS method,the traditional PI control is replaced by the single-neuron PID controller with self-learning ability,and the traditional MRAS is improved.The simulation results show that the improved method is more efficient than the traditional method,and the rapidity of the identification system is improved to a certain extent.Fifthly,the parameter identification results are combined with efficiency optimization,and the optimal flux linkage is modified online by using the identification results to achieve more efficient efficiency optimization control.Compared with the traditional fixed set flux linkage,the improved algorithm can greatly improve the operating efficiency of the motor.Sixth,the validity of the parameter identification method based on Model Reference Adaptive and the efficiency optimization algorithm based on parameter identification is verified by using the experimental circuit built.