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The numerical computation of magnetization processes in moving and rotating assemblies requires the usage of vector hysteresis models. A commonly used model is the so-called Mayergoyz vector Preisach model, which applies the scalar Preisach model into multiple angles of the halfspace. The usage of several scalar models, which are optionally weighted differently, enables the description of isotropic as well as anisotropic materials. The flexibility is achieved, however, at the cost of multiple scalar model evaluations. For solely isotropic materials, two vector Preisach models, based on an extra rotational operator, might offer a lightweight alternative in terms of evaluation cost. The study aims at comparing the three mentioned models with respect to computational efficiency and practical applicability.

The three mentioned vector Preisach models are compared with respect to their computational costs and their representation of magnetic polarization curves measured by a vector vibrating sample magnetometer.

The results prove the applicability of all three models to practical scenarios and show the higher efficiency of the vector models based on rotational operators in terms of computational time.

Although the two vector Preisach models, based on an extra rotational operator, have been proposed in 2012 and 2015, their practical application and inversion has not been tested yet. This paper not only shows the usability of these particular vector Preisach models but also proves the efficiency of a special stageless evaluation approach that was proposed in a former contribution.

In this paper the kinetic behavior of a non‐magnetic cube, plated on two opposite sides with ferromagnetic coating, situated on a horizontal plane surface and immersed in a homogeneous magnetic field is investigated. The created magnetic torque is determined, the involved field quantities are computed applying the integral equation method taking into account the hysteresis of the ferromagnetic coating by a non‐linear iterative procedure based on the Piccard‐Banach fixed point technique. Considering the friction between the piece and the plane surface the equation of motion is solved. The magnetic field strength necessary to rotate the piece in a required direction is determined.

The purpose of this paper is to develop a viscous-type frequency dependent scalar Preisach hysteresis model and to identify the model using measured data and nonlinear numerical field analysis. The hysteresis model must be fast and well applicable in electromagnetic field simulations.

Iron parts of electrical machines are made of non-oriented isotropic ferromagnetic materials. The finite element method (FEM) is usually applied in the numerical field analysis and design of this equipment. The scalar Preisach hysteresis model has been implemented for the simulation of static and dynamic magnetic effects inside the ferromagnetic parts of different electrical equipment.

The comparison between measured and simulated data using a toroidal core shows a good agreement. A modified nonlinear version of TEAM Problem No. 30.a is also shown to test the hysteresis model in the FEM procedure.

The dynamic model is an extension of the static one; an extra magnetic field intensity term is added to the output of the static inverse model. This is a viscosity-type dynamic model. The fixed-point method with stable scheme has been realized to take frequency dependent anomalous losses into account in FEM. This scheme can be used efficiently in the frame of any potential formulations of Maxwell's equations.

This work introduces an efficient and accurate technique to solve the eddy current problem in laminated iron cores considering vector hysteresis.

The mixed multiscale finite element method based on the based on the T,Φ-Φ formulation, with the current vector potential T and the magnetic scalar potential Φ allows the laminated core to be modelled as a single homogeneous block. This means that the individual sheets do not have to be resolved, which saves a lot of computing time and reduces the demands on the computer system enormously.

As a representative numerical example, a single-phase transformer with 4, 20 and 184 sheets is simulated with great success. The eddy current losses of the simulation using the standard finite element method and the simulation using the mixed multiscale finite element method agree very well and the required simulation time is tremendously reduced.

The vector Preisach model is used to account for vector hysteresis and is integrated into the mixed multiscale finite element method for the first time.

Pulse width modulated (PWM) inverters are widely used to feed induction motors for variable speed applications. The use of PWM power supplies induces additional magnetic losses in the magnetic circuit of the electrical machine. The aim of this paper is to present a novel analytical approach to account for these losses.

The methodology proposed here consists in identifying the analytical method with a static Preisach hysteresis model. The Preisach model was validated by comparing it with measurements obtained from an Epstein frame. Then, the results obtained with this approach were compared with a basic analytical method that is widely used.

The authors' model provides a fast way for estimating the minor loop iron losses introduced by static convertors. They compared the proposed model with another analytical model (J. Lavers model) for different wave forms. One can observe that the J. Lavers model overestimates the iron losses introduced by the non‐centred minor loops.

In this paper, an improved analytical model is presented which estimates the non‐centred minor loop iron losses. In order to do a precise estimation of the iron loss introduced by the minor loops, the authors' model takes into account the position and the size of the minor loop. The proposed model is identified from a static Preisach model.

The implementation of a vector Preisach model for the modelling of anisotropic hysteretic soft magnetic materials is outlined. Some comparisons with measurements on alternate and rotational magnetic field excitations are shown. The hysteresis model is inserted inside a two‐dimensional finite element solver formulated in terms of magnetic vector potential and nonlinear solution is handled by means of the fixed point method with H‐scheme. Results obtained on a two‐dimensional geometry are described and discussed.

Widely used in micro‐position devices and vibration control, the piezoelectric actuator exhibits strong hysteresis effects, which can cause inaccuracy and oscillations, even lead to instability. If the hysteretic effects can be predicted, a controller can be designed to correct for these effects. This paper aims to present a neural network hysteresis model with an improved Preisach model to predict the output of piezoelectric actuator.

The improved Preisach model is given: A wiping‐out memory sequence is defined that is along a single axis only and at the same time the ascending and the descending extreme points are separated. The extended area variable is calculated according to wiping‐out memory sequence. The relationship between the two inputs (the extended area variable and variable rate of input signal) and the hysteresis output is implemented with a neural network to approximate the hysteresis model for the piezoelectric actuators.

Some experiments are carried out with a piezoelectric ceramic (PST150/7/40 VS12) and the results show the neural network hysteresis model can reliably predict the hysteretic behaviours in piezoelectric actuators.

The improved Preisach model is a simple model that is implemented by a neural network to reliably predict the hysteretic output in piezoelectric actuators.

The purpose of this paper is to combine the Jiles-Atherton (J-A) hysteresis model with the field separation approach to realize the accurate simulation of dynamic magnetostrictive characteristics of silicon steel sheet.

First, the energy loss of silicon steel sheet is divided into hysteresis loss Why, classical eddy current loss Wed and anomalous loss Wan according to the statistical theory of losses. The Why is calculated by static J-A hysteresis model, Wed and Wan are calculated by the analytical formulae. Then, based on the field separation approach, the dynamic magnetic field is derived. Finally, a new dynamic magnetostrictive model is proposed by means of the quadratic domain rotation model.

Comparison of simulation and experimental results verifies that the proposed model has high accuracy and strong universality.

The proposed method improves the existing method’s problem of relying on too much experimental data, and the method ensures the calculation accuracy, parameter identification accuracy and engineering practicability. Consequently, the presented work greatly facilitates further explorations and studies on simulation of dynamic magnetostrictive characteristics of silicon steel sheet.

Piezoelectric actuators (PEAs) exhibit hysteresis nonlinearity in open-loop operation, which may lead to unwanted inaccuracy and limit system performance. Classical Preisach model is widely used for representing hysteresis but it requires a large number of first-order reversal curves to ensure the model accuracy. All the curves may not be obtained due to the limitations of experimental conditions, and the detachment between the major and minor loops is not taken into account. The purpose of this paper is to propose a modified Preisach model that requires relatively few measurements and that describes the detachment, and then to implement the inverse of the modified model for compensation in PEAs.

The classical Preisach model is modified by adding a derivative term in parallel. The derivative gain is adjusted to an appropriate value so that the measured and predicted hysteresis loops are in good agreement. Subsequently, the new inverse model is similarly implemented by adding another derivative term in parallel with the inverse classical Preisach model, and is then inserted in open-loop operation to compensate the hysteresis. Tracking control experiments are conducted to validate the compensation.

The hysteresis in PEAs can be accurately and conveniently described by using the modified Preisach model. The experimental results prove that the hysteresis effect can be nearly completely compensated.

The proposed modified Preisach model is an effective and convenient mean to characterize accurately the hysteresis. The compensation method by inserting the inverse modified Preisach model in open-loop operation is feasible in practice.

The purpose of this paper is to find out how to model iron losses in electrical machines accurately and efficiently.

The starting point was a previously developed vector hysteresis model that was designed and incorporated into the 2D time‐stepping finite‐element (FE) simulation of induction machines. The developed approach here is a decoupling between the vector hysteresis model and the 2D FE model of the machine. The huge time consumption of the incorporated hysteresis model required some new approach to make the model computationally efficient. This is dealt with through an a posteriori use of the vector hysteresis model.

In this research, it was found that the vector hysteresis model, although used in an a posteriori scheme is able to accurately predict the iron losses as far as these losses are small enough not to affect the other operation characteristics of the machine.

The research methods reported in this paper deal mainly with induction machines. The methods should be applied for transient operations of the induction machines as well as for other types of machines. The fact that the iron losses do not affect very much the operation characteristics of the machine is based on the fact that the air gap field plays a major role in these machines. The method cannot be applied to other magnetic devices where the iron losses are the main loss component.

The paper is of practical value for designers of electrical machines, who use FE programs. The methods presented here allow them to use a different FE package to simulate the machine and own routines (based on the presented methods) to predict the iron losses without loss of accuracy and in a reasonably short time.