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The diagnostics of electrical machines is a very important task. The paper seeks to present a study and analysis of stator winding asymmetry in induction motors. The purpose of this paper is presentation of coupling two numerical techniques, a finite element analysis and an artificial neural network, in diagnostics of electrical machines.

A finite element method (FEM) analysis and time‐stepping are applied for the study of IM with stator winding asymmetry. One of the asymmetry symptoms is an axial flux. In order to determine the level of winding asymmetry a generalized regression neural network has been considered. The result of FFT analysis of axial flux and electromagnetic torque was the input vector to artificial neural network. The output vector is the level of asymmetry. The algorithms are tested using a set data obtained from numerical simulation. The emphasis of this structure is on accurate approximation of the value of the stator winding asymmetry.

The axial flux, as the symptom of stator winding asymmetry, can contribute to better detection of the asymmetry in stator winding.

It is argued that the proposed method based on axial flux and electromagnetic torque is capable of performing detection of the asymmetry in stator winding. The generalized regression neural network can be used in health monitoring system as an inference module.

The axial magnetic field occurs in the end-region of large turbo-generators is known to induce hot points or voltages between laminations, that may cause insulation breakdown and thus stator faults.

It is important to dispose of simple methods for estimating the axial flux rapidly with regard to the operating point of the machine.

The authors provide a practical model of the axial magnetic field based on a simplified vector diagram. The parameters required to build the vector composition of the flux densities are assessed with a limited number of finite element method simulations of the whole end-region of the machine. These simulations were validated by an experimental test on a real turbo-generator. Then the axial flux density was simply estimated for various operating points.

The originality of the paper concerns the practical model of the axial magnetic field based on a simplified vector diagram.

The purpose of this paper is to investigate the theoretical foundation of the so-called quasi 3D modelling method of axial flux machines, and the means for the simulation of the resulting models.

Starting from the first principles, a 3D magnetostatic problem is geometrically decomposed into a coupled system of 2D problems. Genuine 2D problems are derived by decoupling the system. The construction of the 2D simulation models is discussed, and their applicability is evaluated by comparing a finite element implementation to an existing industry-used model.

The quasi 3D method relies on the assumption of vanishing radial magnetic flux. The validity of this assumption is reflected in a residual gained from the 3D coupled system. Moreover, under a modification of the metric of the 2D models, an axial flux machine can be presented as a family of radial flux machines.

The evaluation and interpretation of the residual has not been carried out. Furthermore, the inclusion of eddy currents has not been detailed in the present study.

A summary of existing modelling and simulation methods of axial flux machines is provided. As a novel result, proper mathematical context for the quasi 3D method is given and the underlying assumptions are laid out. The implementation of the 2D models is approached from a general angle, strengthening the foundation for future research.

The purpose of this paper is to suggest a novel current sensor-less drive system for a novel axial flux-switching permanent-magnet motor drive to reduce the costs and avoid problems caused by faults of the current sensors.

Commonly, a conventional controller needs at least two current sensors; in this paper, the current sensors are removed by replacing estimated stator current with the extended Kalman filter.

A prototype of the novel axial flux-switching permanent-magnet motor is fabricated and tested. It is found that the experimental results confirm the proposed method and show that the control has almost the same performance and ability as the conventional control.

The axial flux-switching permanent-magnet motor is one of the most efficient motors, but current sensor-less control of an axial flux-switching permanent-magnet motor with a sandwiched permanent magnet and a unity displacement winding factor has not been specially reported to date. Thus, in this paper, the authors report on current sensor-less control based on the extended Kalman filter for electric vehicles.

To design a high power density machine, an automatic design method is proposed. Hopefully, automatic design method uses only the requirements (torque and speed) and the information about sources (voltage and current).

To calculate the volume, a necessary flux density and an inductance are calculated by the permeance method. All mechanical parameters, stator diameter, teeth width, turn number and so on, realize the necessary flux density and an inductance, and these parameters are expressed as a function of a rotor diameter. By using both conditions of current density and copper loss, a rotor diameter which realizes the minimum volume can be obtained.

As a result of an optimum design, 50 kW SPMSM is realized only into 2[L] spaces, which copper loss is only 500[W], 1 percent of the maximum output. Moreover, 50 kW axial flux type machine is realized only into 1.3[L] spaces. Accurate comparison is possible by only optimum designs because these have the solutions of the same conditions. In a comparison result, a volume of the axial flux machine is less than that of the radial flux machine, because the radial flux type cannot utilize the large rotor diameter. Thus the axial flux type motor is suitable to the high torque machine.

In this research, the length of the coil end and the iron loss, are ignored, because an axial length of stator is much longer than a coil end especially for the high power motor, and the iron loss estimation has not been established.

By using this method, it is possible to perform the automatic design. If a designer inputs only the requested torque, speed and device information, an automatic calculation will be done, and a designer can automatically get a motor structure.

Although some papers can calculate the mechanical parameters which realize only torque, all requirements, torque, speed and power are satisfied in this paper. In addition, an optimum point of the volume is theoretically obtained. In industrial applications, because the power range is very important, especially for electric vehicles and so on, this paper provides more compact and more powerful machines.

The purpose of this paper is the investigation of eddy currents induced in the axial‐flux permanent‐magnet machine housing by the leakage flux and the introduction of permanent magnets in the steady‐state AC finite‐element analysis and coupling their effects with the transient thermal analysis.

The proposed approach is based on the finite‐element method as well as on using the basic analytical equations. The approach was first applied in the magneto transient analyses. Because of the different physical transient‐time constants, the steady‐state AC analysis coupled with transient thermal should be used.

The permanent magnets in the steady‐state AC analysis coupled with the transient thermal analysis can be simulated by coils with an imposed current of a frequency depending on the number of pole pairs and rotation speed. Using any of the electrically conductive materials for the axial‐flux inner slotless stator permanent‐magnet machine housing should be avoided.

The leakage flux induced by permanent magnets and spreading into the axial‐flux permanent‐machine housing is first defined by using the magneto‐transient finite‐element analysis and further used in the steady‐state AC analysis coupled with the transient thermal analyses, all in 3D. Based on the results of these analyses, the temperature distribution in entire machine is calculated and compared with the measurement results.

The purpose of this paper is to exploit the optimal performances of each magnetic material in terms of low iron losses and high saturation flux density to improve the efficiency and the power density of the selected motor.

This paper presents a study to improve the power density and efficiency of e-motors for electric traction applications with high operating speed. The studied machine is a yokeless-stator axial flux permanent magnet synchronous motor with a dual rotor. The methodology consists in using different magnetic materials for an optimal design of the stator and rotor magnetic circuits to improve the motor performance. The candidate magnetic materials, adapted to the constraints of e-mobility, are made of thin laminations of Si-Fe nonoriented grain electrical steel, Si-Fe grain-oriented electrical steel (GOES) and iron-cobalt Permendur electrical steel (Co-Fe).

The mixed GOES-Co-Fe structure allows to reach 10 kW/kg in rated power density and a high efficiency in city driving conditions. This structure allows to make the powertrain less energy consuming in the battery electric vehicles and to reduce CO₂ emissions in hybrid electric vehicles.

The originality of this study lies in the improvement of both power density and efficiency of the electric motor in automotive application by using different magnetic materials through a multiobjective optimization.

The purpose of this paper is to investigate a novel axial flux-switching motor with sandwiched permanent magnet for direct drive electric vehicles (EVs), in which the torque density is increased and the cogging torque is decreased. For reducing the back-electromotive force (EMF) harmonics and cogging torque, a twisted structure is employed. To improve the dynamic performance of the axial field flux-switching sandwiched permanent magnet (AFFSSPM) motor a space vector modulation-direct torque and flux control scheme is proposed.

A multi-objective optimization is performed by means of artificial neural network and non-sorting genetic algorithm II to minimize the cogging torque while preserving the average torque.

A comparative study between two proposed machines and the conventional flux-switching permanent magnet (FSPM) machine is accomplished and the static electromagnetic characteristics are analyzed. It is demonstrated that the proposed model with twisted structure has significantly improved performance over the conventional FSPM machine in back-EMF and efficiency. The proposed controller has a speed loop only and contains neither the current loop nor hysteresis control. The AFFSSPM motor exhibits excellent dynamic performance with this scheme.

The axial flux-switching permanent-magnet machine is one of the most efficient machines but the AFFSSPM with sandwiched permanent magnet has not been specially reported to date. Thus in this paper, the authors report on optimal design of an axial flux-switching sandwiched permanent magnet machine for electric vehicles and investigate its dynamic performance.

To provide a general framework for the electromagnetic analysis of axial flux motors and generators.

The procedure is based on the solution of Maxwell's equation in a cylindrical frame. All field sources (permanent magnets, windings) are subdivided into filamentary windings. The expansion of the 2D air‐gap magnetic field into a Fourier series is computed at every radius. The contributions of the harmonics are then added to achieve the expressions of the stator and rotor flux densities, back emf and developed torque. Slotting and skewing are taken into account also.

The model can be written in a compact form by introducing a generalisation of the space vectors theory. The analysis is proved to be in accordance both with the finite element analysis and with experimental data.

The model does not take into account eddy‐currents and non‐linearities. It does not take into account also specifically 3D phenomena, as the radial components of the flux densities.

The analysis is of practical interest from the standpoint both of control and of machine design. In this latter occurrence, it represents a valid alternative over computationally heavier 3D finite elements models.

Although the procedure is partly based on previous analyses, it is original in the way it exploits the basic theory in order to introduce skewing, slotting, and finite length of the iron. With respect to other models introduced so far, the present one is more compact in the end, its parameters can be easily computed and their physical meaning is easily understood.

Analysis of test data monitored for a number of electric machines from the low volume production line can lead to useful conclusions. The purpose of this paper is to trace the machine performance to find quality-related issues and/or identify assembly process ones. In this paper, the monitoring of experimental data is related to the axial flux motor (AFM) used in hybrid electric vehicle (HEV) and in electric vehicle (EV) traction motors in the global automobile market.

Extensive data analyses raised questions like what could be the causes of possible performance deterioration of the AFM and how many electric motors may not pass requirements during operation tests. In small and medium research units of AFM for HEV or EV, engineers came across a number of serious issues that must be resolved. A number of issues can be eliminated by implementing methods for reducing the number of failing AFMs. For example, improving the motor assembly precision leads to reduction of the machine parameters deterioration.

Assembly tolerances on electric motor characteristics should be investigated during motor design. The presented measurements can be usable and can point out the weakest parts of the motor that can be a reason for the reduced efficiency and/or lifetime of the AFM. Additionally, the paper is addressed to electric motor engineers designing and/or investigating electric AFMs.

Performance of AFM was monitored for a number of identical motors from low volume production line. All tested motors were operated continuously for a long period of time and the tests were repeated every few weeks for half a year to check the reliability of motor design and indicate how much the motor parameters may change. The final results point how many motors fail the requirements of motor performance. A few batches of AFM were selected for testing. Each batch represents a different size (nominal power) of the same type of AFM.