Parameter identification of direct‐drive permanent magnet synchronous generator based on EDMPSO‐EKF

Aiming at the problem that extended Kalman filter (EKF) is difficult to determine appropriate system and measurement noise matrices in parameter identification of direct-drive permanent magnet synchronous generator (D-PMSG), a method D-PMSG based on mean particle swarm optimization with extreme disturbance (EDMPSO)-EKF proposed. Firstly, by analysing principle EKF, dual-thread model established, then (PSO) algorithm improved jump out local optimum adding extremum interference taking average extremum, suitable fitness function designed. Finally, PSO applied adaptive EKF matrix matrix, performs after obtaining optimal matrix. The simulation experiment results show proposed has better convergence speed can more accurately identify parameters stator resistance, inductance flux linkage, it accuracy generalization ability than traditional method.