Optimization of airgap length and capacitive Auxiliary Wind-ing in Three-Phase Induction motors based on a genetic Algo-rithm

Abstract: There is a necessity to design a three-phase squirrel cage induction motor (SCIM) for high-speed application with a larger airgap length in order to limit the distortion of airgap flux density, the thermal expansion of stator and rotor teeth, the centrifugal forces and the magnetic pull. To that effect, a larger airgap length lowers the power factor, efficiency, and torque density of the three-phase SCIM. This should inform motor design engineers to take special care during the design pro-cess of a three-phase SCIM by selecting an airgap length that will provide optimal performance. This paper presents an approach that would assist with the selection of an optimal airgap length (OAL) and optimal capacitive auxiliary stator winding (OCASW) for a high torque per ampere (TPA) three-phase SCIM. Genetic Algorithm (GA) assisted by Finite Element Analysis (FEA) is used in the design process to determine the OAL and OCASW required to obtain high torque per ampere without compromising the merit of achieving an excellent power factor and high efficiency for a three-phase SCIM. The performance of the optimized three-phase SCIM is compared to that of un-optimized machines. The results obtained from FEA are validated through experimental measure-ments. Owing to the penalty functions related to the value of objective and constraint functions introduced in the genetic algorithm model, both FEA and experimental results evidenced that an enhanced torque per ampere three-phase SCIM can be realized for a large OAL, and an OCASW, with high efficiency and excellent power factor through different working conditions