Research on the MTPA Control Method for Permanent Magnet Synchronous Motors Based on Extreme Learning Machine
The parameters of the interior permanent magnet synchronous motor(IPMSM)can vary as the motor operates under different conditions,which will affect the control precision and stability of the electric drive sys-tem.Therefore,it is necessary to perform online identification of the motor parameters.This paper obtains a full-rank system of equations related to resistance,magnetic flux,and inductance by injecting reverse current into the d-axis when Id is zero,and constructs a mathematical model of the motor for identification using the extreme learning machine(ELM)algorithm.The ELM algorithm is then utilized to identify the motor parameters online,and the results are applied to the maximum torque per ampere(MTPA)control system of the IPMSM.The dynam-ic and static performance of the system is tested under different operating conditions of the electric drive system.Simulation experimental results show that under different working conditions,the IPMSM electric drive system exhibits fast dynamic responses in terms of speed,torque,current,small steady-state pulsations,and high system robustness.
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