Swarm Intelligence Algorithm for Induction Motor Field Efficiency Evaluation

Determining induction motor field efficiency is imperative in industries for energy conservation and cost savings. The induction motor efficiency is generally tested in a laboratories by certain methods defined in IEEE Standard – 112. But these methods cannot be used for motor efficiency evaluations in the field because it disrupts the production process of the industry. This paper proposes a swarm intelligence algorithm, Particle Swarm Optimization (PSO) for efficiency evaluation of in-service induction motor based on a modified induction motor equivalent circuit model. In this model, stray load losses are considered. The proposed efficiency evaluation method combines the PSO and the equivalent circuit method. First, the equivalent circuit parameters are estimated by minimizing the difference between measured and calculated values of stator current and input power of the motor using the PSO algorithm. Based on these parameters, the efficiency of the motor at various load points are evaluated by using the equivalent circuit method. To exemplify the performance of the PSO based efficiency estimation method, a 5 HP motor has been tested, compared with genetic algorithm (GA), torque gauge method, equivalent circuit method, slip method, current method and segregated loss method and found to be superior. Accordingly, the method will be useful for engineers who implement the energy efficiency programs to the electric motor systems in industries.