Parameter Identification of Permanent Magnet Synchronous Motor Based on Whale Optimization Algorithm Under Variable Load
A parameter identification method combining stable state identification was proposed to address the problem of poor identification accuracy of the full rank identification model for permanent magnet syn-chronous motors in electrically driven hydraulic power unit under unstable conditions.This method took into account the load variation characteristics of electrically driven hydraulic power unit,identified stable states by real-time calculating the mean square error value within the sliding window,and identified parameters un-der the identified stable state.Using whale optimization algorithm to optimize adjustable parameters for pa-rameter identification,combining adaptive weights to enhance the breadth of early search,and combining simulated annealing algorithm to enhance global search capability.The results show that the accuracy of the stable state recognition method can reach 85%;When the load is constant,the maximum identification error of the improved parameter identification method is 1.46%,and the maximum error of the comparison method is 8.1%;When the load changes,the identification error of the improved parameter identification method can be kept within 3%,eliminating the fluctuation of identification results in the comparison method.
万方数据
维普
