The magnetic field due to a permanent magnet of a tube-side segment as shape and of radial-oriented magnetization is considered. Such a sheet modelling a single pole of the magnet is used to express the suitable contribution to magnetic quantities. A boundary-integral approach is applied that is based on a virtual scalar quantity attributed to the magnet pole. Such an approach leads to express analytically the scalar magnetic potential and the magnetic flux density by means of the elliptic integrals. Numerical examples of the computed fields are given. The general idea of the presented approach is mainly directed towards designing the magnetic field within the air gap of electric machines with permanent magnets as an excitation source. Other technical structures with permanent magnets may be a subject of this approach as well.

The paper presents a methodology for the optimization of a Brushless Direct Current motor (BLDC). In particular it is focused on multiobjective optimization using a genetic algorithm (GA) developed in Matlab/Optimization Toolbox coupled with Maxwell from ANSYS. Optimization process was divided into two steps. The aim of the first one was to maximize the RMS torque value and to minimize the mass. The second part of the optimization process was to minimize the cogging torque by selecting proper magnet angle. The paper presents the methodology and capabilities of scripting methods rather than specific optimization results for the applied geometry.

The calculation results of the static field parameters for permanent magnet linear synchronous motor have been presented in this work. The influence of the construction temperature on the parameters has been analyzed mathematically. Models for magnetic and temperature fields determination have been formulated. Two kinds of permanent magnets (NdFeB and SmCo) have been considered. The distribution of the thermal field has been obtained using the finite element method (FEM).

This paper presents a review of the electromagnetic field and a performance analysis of a radial flux interior permanent magnet (IPM) machine designed to achieve 80 kW and 125 Nmfor an electric and hybrid traction vehicle. The motor consists of a 12-slot stator with a three-phase concentrated winding as well as an 8-pole rotor with V-shaped magnets. Selected motor parameters obtained from an IPM prototype were compared with the design requirements. Based on the electromagnetic field analysis, the authors have indicated the parts of the motor that should be redesigned, including the structure of the rotor core, aimed at enhancing the motor’s performance and adjusting segmentation for magnet eddy current loss reduction. In addition, iron and PM eddy current losses were investigated. Moreover, transient analysis of current peak value showed that the current may increase significantly compared to steady-state values.Amap of transient peak current load vs. torque load plotted against rotor speed was provided. Based on the numeric and analytical results of physical machine parameters, the authors indicate that collapse load during the motor’s operation may significantly increase the risk of permanent magnet (PM) demagnetization. It was also found that collapse load increases the transient torque, which may reduce the lifetime of windings.

Accurate demagnetization modelling is mandatory for a reliable design of rare-earth permanent magnet applications, such as e.g. synchronous machines. The magnetization of rare-earth permanent magnets requires high magnetizing fields. For technical reasons, it is not always possible to completely and homogeneously achieve the required field strength during a pulse magnetization, due to stray fields or eddy currents. Not sufficiently magnetized magnets lose remanence as well as coercivity and the demagnetization characteristic becomes strongly nonlinear. It is state of the art to treat demagnetization curves as linear. This paper presents an approach to model the nonlinear demagnetization in dependence on the magnetization field strength. Measurements of magnetization dependent demagnetization characteristics of rare-earth permanent magnets are compared to an analytical model description. The physical meaning of the model parameters and the influence on them by incomplete magnetization are discussed for different rare-earth permanent magnet materials. Basically, the analytic function is able to map the occurring magnetization dependent demagnetization behavior. However, if the magnetization is incomplete, the model parameters have a strong nonlinear behavior and can only be partially attributed to physical effects. As a benefit the model can represent nonlinear demagnetization using a few parameters only. The original analytical model is from literature but has been adapted for the incomplete magnetization. The discussed effect is not sufficiently accurate modelled in literature. The sparse data in literature has been supplemented with additional pulsed-field magnetometer measurements.

This paper deals with the finite element analysis of the demagnetization process of the line start permanent magnet synchronous motor. Special attention has been paid to demagnetization risk assessment after resynchronization during a short-term supply power outage. The current and torque waveforms have been determined assuming the difference depending initial rotor position angle. It has been demonstrated that the highest demagnetization risk occurs when resynchronization (motor reclosing) is performed whe induced electromotive forces are in anti-phase to the supply voltage waveforms. The effect of cage winding resistance on the risk of demagnetization is examined and discussed.

The multi-phase permanent-magnet machines with a fractional-slot concentrated-winding (FSCW) are a suitable choice for certain purposes like aircraft, marine, and electric vehicles, because of the fault tolerance and high power density capability. The paper aims to design, optimize and prototype a five-phase fractional-slot concentrated-winding surface-mounted permanent-magnet motor. To optimize the designed multi-phase motor a multi-objective optimization technique based on the genetic algorithm method is applied. The machine design objectives are to maximize torque density of the motor and maximize efficiency then to determine the best choice of the designed machine parameters. Then, the two-dimensional Finite Element Method (2D-FEM) is employed to verify the performance of the optimized machine. Finally, the optimized machine is prototyped. The paper found that the results of the prototyped machine validate the results of theatrical analyses of the machine and accurate consideration of the parameters improved the acting of the machine.

The aim of the studywas to find an effective method of ripple torque compensation for a direct drive with a permanent magnet synchronous motor (PMSM) without time-consuming drive identification. The main objective of the research on the development of a methodology for the proper teaching a neural network was achieved by the use of iterative learning control (ILC), correct estimation of torque and spline interpolation. The paper presents the structure of the drive system and the method of its tuning in order to reduce the torque ripple, which has a significant effect on the uneven speed of the servo drive. The proposed structure of the PMSM in the dq axis is equipped with a neural compensator. The introduced iterative learning control was based on the estimation of the ripple torque and spline interpolation. The structurewas analyzed and verified by simulation and experimental tests. The elaborated structure of the drive system and method of its tuning can be easily used by applying a microprocessor system available now on the market. The proposed control solution can be made without time-consuming drive identification, which can have a great practical advantage. The article presents a new approach to proper neural network training in cooperation with iterative learning for repetitive motion systems without time-consuming identification of the motor.

When the machine is at high speed, serious problems occur, such as high frequency loss, difficult thermal management, and the rotor structural strength insufficiency. In this paper, the performances of two high-speed permanent magnet generators (HSP- MGs) with different rotational speeds and the same torque are compared and analyzed. The two-dimensional finite element model (FEM) of the 117 kW, 60 000 rpm HSPMG is established. By comparing a calculation result and test data, the accuracy of the model is verified. On this basis, the 40 kW, 20 000 rpm HSPMG is designed and the FEM is established. The relationship between the voltage regulation sensitivity and power factor of the two HSPMGs is determined. The influence mechanism of the voltage regulation sensitivity is further revealed. In addition, the air-gap flux density is decomposed by the Fourier transform principle, and the influence degree of different harmonic orders on the HSPMG performance is determined. The method to reduce the harmonic content is further proposed. Finally, the method to improve the HSPMG overload capacity is obtained by studying the maximum power. The research showed that the HSPMG at low speed (20 000 rpm) has high sensitivity of the voltage regulation, while the HSPMG at high speed (60 000 rpm) is superior to the HSPMG at low speed in reducing the harmonic content and increasing the overload capacity.

In this study, the optimization of air gap magnetic flux density of open slotted axial flux permanent magnet (AFPM) machine which was developed for wind turbine has been obtained using the Taguchi experimental method. For this, magnetic analyzes were performed by ANSYS Maxwell program according to Taguchi table. Then the optimum values have been determined and the average magnetic flux density values have been calculated for air gap and iron core under load and no-load conditions with ANSYS Maxwell. Traditionally, 15625 analyzes are required for 6 independent variables and 5 levels when experimental method is used. In this study, optimum values are determined by 25 magnetic analyzes, which use L25 orthogonal array. For this purpose, both factor effect graph and signal to noise ratios are used, according to the factors and levels which are obtained from the factor effect graph and the signal to noise ratio. Parameters are re-analyzed by Maxwell. The optimum factors and levels are determined. For optimized values, the air gap magnetic flux density is improved by 65.7% and 173.26%, respectively, according to the average value and the initial design. Therefore, the variables are optimized in a shorter time with Taguchi experimental design method instead of the traditional design method for open slotted AFPM generator. In addition, the results were analyzed statistically using ANOVA and Regression model. The variables were found to be significant by ANOVA. The degree of influence of the variables on the air gap magnetic flux density was also determined by the Regression model.