Search results

The purpose of this paper is to investigate the convective heat transfer of magnetic nanofluid (MNF) inside a square enclosure under uniform magnetic fields considering nonlinearity of magnetic field-dependent thermal conductivity.

The properties of the MNF (Fe₃O₄+kerosene) were described by polynomial functions of magnetic field-dependent thermal conductivity. The effect of the transverse magnetic field (0 < H < 10⁵), Hartmann Number (0 < Ha < 60), Rayleigh number (10 <Ra <10⁵) and the solid volume fraction (0 < φ < 4.7%) on the heat transfer performance inside the enclosed space was examined. Continuity, momentum and energy equations were solved using the finite element method.

The results show that the Nusselt number increases when the Rayleigh number increases. In contrast, the convective heat transfer rate decreases when the Hartmann number increases due to the strong magnetic field which suppresses the buoyancy force. Also, a significant improvement in the heat transfer rate is observed when the magnetic field is applied and φ = 4.7% (I = 11.90%, I = 16.73%, I = 10.07% and I = 12.70%).

The present numerical study was carried out for a steady, laminar and two-dimensional flow inside the square enclosure. Also, properties of the MNF are assumed to be constant (except thermal conductivity) under magnetic field.

The results can be used in thermal storage and cooling of electronic devices such as lithium-ion batteries during charging and discharging processes.

The accuracy of results and heat transfer enhancement having magnetic field-field-dependent thermal conductivity are noticeable. The results can be used for different applications to improve the heat transfer rate and enhance the efficiency of a system.

This paper aims to propose a novel mathematical model of bearingless switched reluctance motor (BSRM). This model differs from conventional mathematical models in the calculation of torque and suspension forces. Conventional mathematical models neglect the coupling relationship between the α- and β-axes or ignore the magnetic saturation of the Si-Fe material. This study considers these issues simultaneously. Additionally, considering the air-gap edge effect, the fringing coefficient is used to establish a high-precision mathematical model.

An innovative mathematical model of BSRM based on the Maxwell stress method was established by selecting an appropriate integration path. The fringing coefficient of the air-gap was computed based on the finite element analysis results at the aligned position of the stator and rotor poles. Using the least squares fitting method, the piecewise fitted magnetization curve of the Si-Fe material was utilized to calculate flux density.

The appropriate integration path of the Maxwell stress method was selected, which considered the coupling relationship of the suspension forces in the α- and β-axes and was closer to the actual situation. The fringing coefficient of the air-gap improved the calculation accuracy of air-gap flux density. The magnetomotive force was consumed by the magnetic resistance of the stator and rotor poles considering the magnetic saturation.

A novel mathematical model of BSRM is proposed. Different from conventional mathematical models, the proposed model can effectively solve the coupling relationship of the suspension forces in the α- and β-axes. Additionally, this model is consistent with the actual situation of motor as it includes a reasonable calculation of the air-gap flux density, considering the air-gap edge effect and magnetic saturation.

The ordinary vector hysteresis stop model with constant threshold values is not able to prohibit the hysteretic property after the saturation correctly. This paper aims to develop an improved vector hysteresis stop model with threshold surfaces. This advanced anisotropic vector hysteresis stop model can represent the magnetic saturation properties and the hysteresis losses under alternating and rotating magnetizations.

By integrating anhysteretic surfaces into the elastic element of a vector hysteresis stop model, the anisotropy of the permeability of an electrical steel sheet can be represented. Instead of the commonly used constant threshold value for plastic elements of the hysteresis model, threshold surfaces are applied to the stop hysterons. The threshold surfaces can be derived directly from measured alternating major loops of the material sample. By saturated polarization, the constructed threshold surfaces are vanishing. In this way, the reversible magnetic flux density is in the same direction of the applied magnetic flux density. Thus, the saturation properties are satisfied.

Analyzing the measurements of the electrical steel sheets sample obtained from a rotational single sheet tester shows that the clockwise (CW) and counter-CW (CCW) rotational hysteresis losses decrease by saturated flux density. At this state, instead of the domain wall motion, the magnetization rotation is dominant in the material. As a result, the hysteresis losses, which are related to the domain wall motion, are vanished near the saturation. In one stop operator, the plastic element represents the hysteresis part of the model. Integrating threshold surface into the plastic element, the hysteresis part can be modified to zero near the saturation to represent the saturation properties.

The results of this work demonstrate that the presented vector hysteresis stop model allows simulation of anisotropic hysteresis effects, alternating and rotating hysteresis losses. The parameters of the hysteresis model are determined by comparing the measured and modeled minor loops in different alternating magnetization directions. With the identified parameters, the proposed model is excited with rotated excitations in CW and CCW directions. The rotated hysteresis losses, derived from the model, are then compared with those experimentally measured. The modified vector stop model can significantly improve the accuracy of representing hysteresis saturations and losses.

This paper aims to omit the difficulties of directly finding the periodic steady-state solutions for electromagnetic devices described by circuit models.

Determine the discrete integral operator of periodic functions and develop an iterative algorithm determining steady-state solutions by a multiplication of matrices only.

An alternative method to creating finite-difference relations directly determining steady-state solutions in the time domain.

Reduction of software and hardware requirements for determining steady-states of electromagnetic.

A unified approach for directly finding steady-state solutions for ordinary nonlinear differential equations presented in the normal form.

Eliminate the necessity of solving high-order finite-difference equations for steady-state analysis of electromagnetic devices described by circuit models.

The first purpose of this paper is to identify – by an inverse problem – the unknown material characteristics in a permanent magnet synchronous machine in order to obtain a numerical model that is a realistic representation of the machine. The second purpose is to optimize the machine geometrically – using the accurate numerical model – for a maximal torque to losses ratio. Using the optimized geometry, a new machine can be manufactured that is more efficient than the original.

A 2D finite element model of the machine is built, using a nonlinear material characteristic that contains three parameters. The parameters are identified by an inverse problem, starting from torque measurements. The validation is based on local BH‐measurements on the stator iron.

Geometrical parameters of the motor are optimized at small load (low‐stator currents) and at full load (high‐stator currents). If the optimization is carried out for a small load, the stator teeth are chosen wider in order to reduce iron loss. An optimization at full load results in a larger copper section so that the copper loss is reduced.

The identification of the material parameters is influenced by the tolerance on the air gap – shown by a sensitivity analysis in the paper – and by 3D effects, which are not taken into account in the 2D model.

The identification of the material parameters guarantees that the numerical model describes the real material properties in the machine, which may be different from the properties given by the manufacturer because of mechanical stress and material degradation.

The optimization is more accurate because the material properties, used in the numerical model, are determined by the solution of an inverse problem that uses measurements on the machine.

The dynamic model of radial active magnetic bearings, which is based on the current and position dependent partial derivatives of flux linkages and radial force characteristics, is determined using the finite element method. In this way, magnetic nonlinearities and cross‐coupling effects are considered more completely than in similar dynamic models. The presented results show that magnetic nonlinearities and cross‐coupling effects can change the electromotive forces considerably. These disturbing effects have been determined and can be incorporated into the real‐time realization of nonlinear control in order to achieve cross‐coupling compensations.

The purpose of this paper is to solve efficiently the topology optimization (TO) in time domain problem with magnetic nonlinearity requiring a large-scale finite element mesh. As an actual application model, the proposed method is applied to induction heating apparatus.

To achieve TO with efficient computation time, a multistage topology is proposed. This method can derive the optimum structure by repeatedly reducing the design domain and regenerating the finite element mesh.

It was clarified that the structure derived from proposed method can be similar to the structure derived from the conventional method, and that the computation time can be made more efficient by parameter tuning of the frequency and volume constraint value. In addition, as a time domain induction heating apparatus problem of an actual application model, an optimum topology considering magnetic nonlinearity was derived from the proposed method.

Whereas the entire design domain must be filled with small triangles in the conventional TO method, the proposed method requires finer mesh division of only the stepwise-reduced design domain. Therefore, the mesh scale is reduced, and there is a possibility that the computation time for TO can be shortened.

The paper describes how the classical formula of the Maxwell magnetic stress tensor may be extended to cover the magnetostriction phenomena. It is assumed that the ferromagnetic continuum is isotropic and conservative. The method takes into account the magnetic nonlinearity and it assumes that mechanical deflections are sufficiently small to neglect the nonlinearity of the Hooke's law. The paper presents also the experimental method, which has been used to measure the magnetostriction intensity for electrotechnical laminations. As the final result, the distribution of the volume magnetostriction forces acting on the stator core of the induction motor has been calculated.

The density method is one of the powerful topology optimization methods of magnetic devices. The density method has the advantage that it has a high degree of freedom of shape expression which results in a high-performance design. On the other hand, it has also the drawback that unsuitable shapes for actually manufacturing are likely to be generated, e.g. checkerboards or grayscale. The purpose of this paper is to develop a method that enables topology optimization suitable for fabrication while taking advantage of the density method.

This study proposes a novel topology optimization method that combines convolutional neural network (CNN) as an effective smoothing filter with the density method and apply the method to the shield design with magnetic nonlinearity.

This study demonstrated some numerical examples verifying that the proposed method enables to efficiently obtain a smooth and easy-to-manufacture shield shape with high shielding ability. A network architecture suitable as smoothing filter was also exemplified.

In the field of magnetic field analysis, very few studies have verified the usefulness of smoothing by using CNN in the topology optimization of magnetic devices. This paper develops a novel topology optimization method that skillfully combines CNN with the nonlinear magnetic field analysis and also clarifies a suitable network architecture that makes it possible to obtain a target device shape that is easy to manufacture while minimizing the objective function value.

Gradient coils designed by conventional target field methods usually have a complex physical structure and these methods are not convergent for complex routing area problems. This study aims to design a multi-coil (MC) gradient system arranged on a complex routing area including two cylindrical surfaces with different radii for a head magnetic resonance imaging scanner.

A MC system model is established. In this model, the sub-coils are evenly distributed on two cylindrical wiring surfaces, and the radii of coils are the same on one cylindrical surface. With the target magnetic field set, the currents in every individual coil are solved by constrained least-squares fitting based on the Levenberg–Marquardt method.

The magnetic field nonlinearity generated by designed coils is validated as 4.50% and 3.57% for X-gradient coil and Z-gradient coil, respectively, which satisfy the mainstream nonlinearity standards. The analysis of the optimization results indicates that hardware requirements can be considerably reduced by connecting coils with the same currents in series.

High-linearity gradient magnetic fields are generated on complex routing areas by adopting the MC structure. In addition, the requirements for current sources and amplifiers are considerably reduced.