Estimation of induction motor equivalent circuit parameters and losses from transient measurement

Abstract

Due to robustness and low-cost, Induction motors are among the most commonly utilized types of motors in industrial applications. The operation and efficiency of any induction motor can be predicted with reasonable accuracy by solving its equivalent circuit. However, the equivalent circuit parameters may differ from the measured one with aging and when the operating conditions varies. So, it would be advantageous, if the motor parameters can be estimated by a simple and cost-effective method under running condition. Within this research, the circuit model parameters, motor losses, applied load torque and rotor inertia of a 3-phase induction motor at various loads have been estimated applying Particle Swarm Optimization (PSO) technique, from the measured transient current and supply voltage. Using the estimated quantities, various performance indicators were assessed. The predicted operational metrics were evaluated against the corresponding recorded experimental values. The comparison revealed negligible errors, establishing the reliability of the proposed method. In practical applications, the developed algorithm seems promising for predicting:

• (a)
  The control parameters associated with power electronic drives driving the induction motor.
• (b)
  The proposed parameter estimation technique, with appropriate modifications, could significantly contribute in the domain of fault classification for induction motors.
• (c)
  With the help of thermal models, this research work is capable of developing a temperature based predictive condition monitoring scheme for induction motors.
• (d)
  It has the potential to revolutionize the approach to motor monitoring, potentially enhancing operational efficiency, reliability, and lifespan.