An online parameter estimation using current injection with intelligent current-loop control for ipmsm drives

Faa Jeng Lin*, Syuan Yi Chen, Wei Ting Lin, Chih Wei Liu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


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.

Original languageEnglish
Article number8138
Issue number23
Publication statusPublished - 2021 Dec 1


  • D-axis current injection
  • Interior permanent magnet synchronous motor (IPMSM)
  • Maximum torque per ampere (MTPA)
  • Online parameter estimation
  • Proportional-integral-derivative (PID) neural network
  • Recursive least square (RLS)

ASJC Scopus subject areas

  • Control and Optimization
  • Energy (miscellaneous)
  • Engineering (miscellaneous)
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Fuel Technology
  • Renewable Energy, Sustainability and the Environment


Dive into the research topics of 'An online parameter estimation using current injection with intelligent current-loop control for ipmsm drives'. Together they form a unique fingerprint.

Cite this