Parameter Estimation of Isotropic PMSMs Based on Multiple Steady-State Measurements Collected During Regular Operations

Elia Brescia, Paolo Roberto Massenio, Mauro Di Nardo, Giuseppe Leonardo Cascella, Chris Gerada, Francesco Cupertino

Research output: Journal PublicationArticlepeer-review


This paper proposes a novel method to estimate the parameters of isotropic PMSMs which uses only steady-state measurements of load conditions commonly available during the regular operations of off-the-shelf industrial drives. Differently from existing online and offline approaches, the proposed method is designed considering real-world scenarios where ad-hoc tests, additional sensors and the implementation of custom software procedures, such as signal injection, are highly discouraged. The rotor flux linkage, the stator resistance and inductance are estimated with the aid of Adaline neural networks using two operating conditions of the motor. Considering parameter variations according to the actual operating conditions as well as the influence of the inverter nonlinearity and actuation delay, the estimation errors are minimized by proper selecting these two optimal conditions. The accuracy of the proposed method is validated by simulation and experimental studies considering scenarios with different number of motor operating conditions.

Original languageEnglish
Pages (from-to)1-16
Number of pages16
JournalIEEE Transactions on Energy Conversion
Publication statusAccepted/In press - 2023


  • Actuation delay compensation
  • adaline neural network
  • Couplings
  • Delays
  • Estimation
  • inverter nonlinearity
  • large scale application
  • parameter estimation
  • rank deficiency
  • Rotors
  • Steady-state
  • synchronous machines
  • Synchronous motors
  • Voltage measurement

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering


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