Influence of the shape of squirrel-cage bars on the dimensions of permanent magnets in an optimized line-start permanent magnet synchronous motor

Abstract

Purpose The purpose of this paper is to compare parameters and properties of optimal structures of a line-start permanent magnet synchronous motor (LSPMSM) for the cage winding of a different rotor bar shape. Design/methodology/approach The mathematical model of the considered motor includes the equation of the electromagnetic field, the electric circuit equations and equation of mechanical equilibrium. The numerical implementation is based on finite element method (FEM) and step-by-step algorithm. To improve the particle swarm optimization (PSO) algorithm convergence, the velocity equation in the classical PSO method is supplemented by an additional term. This term represents the location of the center of mass of the swarm. The modified particle swarm algorithm (PSO-MC) has been used in the optimization calculations. Findings The LSPMSM with drop type bars has better performance and synchronization parameters than motors with circular bars. It is also proved that the used modification of the classical PSO procedure ensures faster convergence for solving the problem of optimization LSPMSM. This modification is particularly useful when the field model of phenomena is used. Originality/value The authors noticed that to obtain the maximum power factor and efficiency of the LSPMSM, the designer should take into account dimensions and the placement of the magnets in the designing process. In the authors’ opinion, the equivalent circuit models can be used only at the preliminary stage of the designing of line-start permanent magnet motors.

Methodology for Cage Shape Optimization of a Permanent Magnet Synchronous Motor Under Line Start Conditions

“…Lumped parameter models are typically used for analysis [2]. Unfortunately, such models tend to be unreliable, especially in the context of the transient state during starting; hence, their usefulness is very limited for design optimization purposes.…”

“…In the proposed algorithm, a term is added to (1) which describes the center of gravity of the swarm c 3 r 3 x mc − x i k−1 (2) where c 3 is the learning factor, r 3 is the random number, and x mc is the vector of coordinates of the gravity of the swarm.…”

“…The parameters resulting in the best starting performance of the line start permanent magnet synchronous motor motor (LSPMSM) are normally different to the optimal design for synchronous operation (efficiency and power factor) [1], [2], thus it is advisable to conduct a multiobjective search to account for all conflicting requirements. This type of optimization is very time consuming if full numerical modeling is used; in this paper, efficient design strategies are considered as well as ways of extracting motor parameters from field solutions.…”

“…An algorithm is developed to establishvia parallel computation-such parameters, primarily the synchronous torque and the synchronizing torque during starting. The methodology first proposed in [2] has been adapted relying on numerical field solutions using finite-element modeling at an imposed speed.…”

Optimal design of the rotor geometry of line-start permanent magnet synchronous motor using the bat algorithm

“…The exciting system was described with the use of three design variables: s 1 = lm -permanent magnet width, s 2 = gm -the thickness of the magnet and s 3 = rm -distance between the poles. All design variables s j in the optimization process have been transformed into dimensionless quantities x j using the following formula [15]:…”