Łukasz Knypiński

Optimization of the permanent magnet brushless DC motor employing finite element method

Purpose – The purpose of this paper is to elaborate the algorithm and computer code for the structure optimization of the outer rotor permanent magnet brushless DC motor and to execute optimization of selected motor structure using the non‐deterministic procedure.Design/methodology/approach – The mathematical model of the device includes the electromagnetic field equations with the nonlinearity of the magnetic core taken into account. The numerical implementation is based on the finite element method and stepping procedure. The genetic algorithm has been applied for the optimization. The computer code has been elaborated.Findings – The elaborated computer software has been applied for the optimization and design of BLDC motors. The elaborated algorithm has been tested and a good convergence has been attained.Originality/value – The presented approach and computer software can be successfully applied to the design and optimization of different structure of BLDC motors.

Optimization of the rotor geometry of the line-start permanent magnet synchronous motor by the use of particle swarm optimization

Purpose – The purpose of this paper is to elaborate the methodology and software for the optimization of rotor structure of the line-start permanent magnet synchronous motor (LSPMSM). To prove usefulness of presented approach the case study problem has been solved. Design/methodology/approach – The modified particle swarm optimization (PSO) algorithm has been employed for the optimization of LSPMSM. The optimization solver has been elaborated in Delphi environment. The software consists of two modules: an optimization solver and a numerical model of LSPMSM. The model of the considered machine has been developed in the ANSYS Maxwell environment. In the optimization procedure the objective function has been based on maximizing efficiency and power factor. Findings – Obtained results show that modified PSO algorithm can be successfully applied for the optimization of the rotor structure of LSPMSM. This software can be used as a design tool to improve the performance of LSPMSM. The results of studied case pro...

Decomposition of the compromise objective function in the permanent magnet synchronous motor optimization

Purpose – The purpose of this paper is to elaborate an algorithm and the computer code for the optimization of the permanent magnet synchronous motor (PMSM) including the shaft torque, the cogging torque, the total harmonic distortion factor of the back EMF and magnet volume into compromise objective function. Design/methodology/approach – The mathematical model of the device includes the magnetic field equations with the nonlinearity of the magnetic core taken into account. The numerical implementation is based on the finite element method (FEM) and time stepping procedure. The genetic algorithm has been applied for the optimization. The comprehensive computer code containing the FEM model and optimization procedures have been elaborated. Findings – Very important problem at formulating the optimization task is the choice of the functional parameters which constitute the objective and constraint functions. In the paper it has been shown that uncritical constructing the objective function could lead to ir...

Field‐circuit simulation of the dynamics of the outer rotor permanent magnet brushless DC motor

Purpose – The purpose of this paper is to elaborate a mathematical model of dynamic operation of the permanent magnet brushless DC (BLDC) motor with outer rotor and investigate the influence of magnets width on the dynamic parameters.Design/methodology/approach – The mathematical model of the devices includes: the equation of the electromagnetic field, the electric circuit equations and equation of mechanical motion. In elaborated algorithm, all these equations are coupled – therefore they are solved simultaneously. The numerical implementation is based on finite element method and step‐by‐step algorithm. The non‐linear‐coupled field‐circuit equations have been solved by using the Newton‐Raphson algorithm. The computer code for dynamics simulation of the machine has been developed.Findings – The elaborated algorithm and the computer code have been applied for the 2D simulation of BLDC motor dynamics. The algorithm has a good convergence and its usefulness was proved. Various results of the analysis are pr...

Optimization of the synchronous motor with hybrid permanent magnet excitation system

Purpose – The purpose of this paper is to elaborate an algorithm and the software for the rotor structure optimization of the permanent magnet synchronous motor (PMSM) with a magnet composed of two materials made with the use of different technologies: sintered Neodymium magnets and powder dielectromagnets. To execute of optimization of selected motor structure using the non-deterministic procedure. Design/methodology/approach – The mathematical model of the devices includes: the equation of the electromagnetic field, the electric circuit equations and equation of mechanical motion. The numerical implementation is based on finite element method and step-by-step algorithm. The genetic algorithm has been applied in the optimization procedures. The computer code has been developed. Findings – The elaborated computer software has been applied for the optimization and design of PMSMs. The elaborated algorithm has been tested and a good convergence has been attained. The parameters of two optimal structures of ...

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

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.

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

Abstract In this paper an algorithm for the optimization of excitation system of line-start permanent magnet synchronous motors will be presented. For the basis of this algorithm, software was developed in the Borland Delphi environment. The software consists of two independent modules: an optimization solver, and a module including the mathematical model of a synchronous motor with a self-start ability. The optimization module contains the bat algorithm procedure. The mathematical model of the motor has been developed in an Ansys Maxwell environment. In order to determine the functional parameters of the motor, additional scripts in Visual Basic language were developed. Selected results of the optimization calculation are presented and compared with results for the particle swarm optimization algorithm.