An Online Parameter Estimation Using Current Injection with Intelligent Current-Loop Control for IPMSM Drives

Faa-Jeng Lin, Syuan-Yi Chen, Wei-Ting Lin and Chih-Wei Liu
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Faa-Jeng Lin: Department of Electrical Engineering, National Central University, Chungli 320, Taiwan
Syuan-Yi Chen: Department of Electrical Engineering, National Taiwan Normal University, Taipei 106, Taiwan
Wei-Ting Lin: Department of Electrical Engineering, National Central University, Chungli 320, Taiwan
Chih-Wei Liu: Department of Electrical Engineering, National Central University, Chungli 320, Taiwan

Energies, 2021, vol. 14, issue 23, 1-21

Abstract: An online parameter estimation methodology using the d -axis current injection, which can estimate the distorted voltage of the current-controlled voltage source inverter (CCVSI), the varying dq -axis 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 d -axis current injection-based parameter estimation methodology considering the nonlinearity of a CCVSI is proposed. Then, during current injection, a simple linear model is developed to model the cross- and self-saturation of the dq -axis inductances. Since the d -axis unsaturated inductance is difficult to obtain by merely using the recursive least square (RLS) method, a novel tuning method for the d -axis 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 proportional-integral-derivative (PID) neural network controller with improved online learning algorithm is adopted to replace the traditional PI controller. The estimated the dq -axis 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.

Keywords: online parameter estimation; d -axis current injection; interior permanent magnet synchronous motor (IPMSM); recursive least square (RLS); maximum torque per ampere (MTPA); proportional-integral-derivative (PID) neural network (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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