Dynamic PSO Algorithm Based In-Situ Induction Motor Efficiency Determination

Abstract

Three-phase cage induction motors consume almost two-thirds of the electricity generated. Replacing inefficient working induction motors with more effective ones leads to important energy savings. It is therefore necessary to develop a fresh effectiveness determination technique for in-situ induction motor (ISIM). IEEE standard 112 techniques that require no-load and locked rotor experiments can determine the efficiency of the induction engine. For the ISIM, these tests are not feasible. This article proposes a novel implementation of the Dynamic Particle Swarm Optimization (DPSO) algorithm to estimate the ISIM's effectiveness. In DPSO, the inertia weight is dynamically altered based on the particles ' highest fitness value to promote the worldwide particle exploration capacity at the start of the algorithm and provide the worldwide optima at the end point. The suggested technique utilizes the ISIM's measuring information of stator voltage, stator current, stator strength, power factor, input energy, and rotor velocity. The DPSO algorithm is used to assess the parameters of the engine equivalent circuit by minimizing the mistake between the determined and measured information instead of using no-load and blocked rotor tests. The effectiveness of the in-situ induction motor is then estimated using modified equivalent circuit model that involves stray load losses. The efficacy of the suggested algorithm has been tested on a 5 HP engine. The outcomes of the simulation acquired are contrasted with the equivalent circuit technique (ECM) and PSO algorithm. The findings show that the DPSO algorithm is better than the other comparative methods to determine the ISIM's effectiveness.