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Abstract
An online parameter estimation methodology using the daxis current injection, which can estimate the distorted voltage of the currentcontrolled voltage source inverter (CCVSI), the varying dqaxis inductances, and the rotor flux, is proposed in this study for interior permanent magnet synchronous motor (IPMSM) drives in the constant torque region. First, a daxis current injectionbased parameter estimation methodology considering the nonlinearity of a CCVSI is proposed. Then, during current injection, a simple linear model is developed to model the crossand selfsaturation of the dqaxis inductances. Since the daxis unsaturated inductance is difficult to obtain by merely using the recursive least square (RLS) method, a novel tuning method for the daxis unsaturated inductance is proposed by using the theory of the maximum torque per ampere (MTPA) with the combination of the RLS method. Moreover, to improve the bandwidth of the current loop, an intelligent proportionalintegralderivative (PID) neural network controller with improved online learning algorithm is adopted to replace the traditional PI controller. The estimated the dqaxis inductances and the rotor flux are adopted in the decoupled control of the current loops. Finally, the experimental results at various operating conditions of the IPMSM in the constant torque region are given.
Original language  English 

Article number  8138 
Journal  Energies 
Volume  14 
Issue number  23 
DOIs  
State  Published  1 Dec 2021 
Keywords
 Daxis current injection
 Interior permanent magnet synchronous motor (IPMSM)
 Maximum torque per ampere (MTPA)
 Online parameter estimation
 Proportionalintegralderivative (PID) neural network
 Recursive least square (RLS)
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 1 Finished

Intelligent HighPerformance Interior Permanent Magnet Synchronous Motor Drive System(2/3)
1/08/21 → 31/07/22
Project: Research