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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.

In order to reduce CO₂ emissions of new cars many hydraulic and mechanical systems like e.g.: water pump, oil pump, power steering, clime compressor have been exchanged with pure electromechanical systems, which are driven only on request. This helps to reduce fuel consumption. This trend requires of utilization of modern brushless electric motors, which are controlled from power electronic control unit – ECU. In today's car can be found between 30 to 150 electric motors. Many of them are still simple brush type with ferrite magnets. Also in this area, drift in the direction of brushless motors can bee seen, because of higher efficiency, longer lifetime, lower noise, better EMC and more controllable torque vs speed characteristic. There are different technological solutions, which can been used in the area of brushless motors in order to reduce size and cost of single component. One major factor of BLDC/AC motor is rear earth permanent magnet material used during production. A magnet material cost could be in the range from 30 percent (basis price 2010) up to 90 percent (basis price 2011) of total material motor cost, depends on actual rear earth material price level. In order to reduce magnet cost, the aim of this paper is to find the most robust motor design, which can be resistant against maximum temperature and phase current amplitude for the same magnet material properties, coercive force – Hcj. This behaviour is called demagnetization property.

Analysis was performed based on review of literature, own theoretical and practical research and experience in the area of electromechanical systems for automotive application. During motor analysis computer numerical simulation method, CAD and experiment were used.

As a result, comparison of different motors' topologies with different properties of magnet materials is presented. The worked out methodology shows very good correlation between simulations and measurements. This work can be used in order to reduce test effort and reduce cost of design.

The presented methodology reduces for new designs test effort and development cost and gives an implication of robust motor topology for demagnetization effects.

It is the first paper where demagnetization effects have been studied theoretically and in laboratory in order to find the most robust design, reduce magnet cost by reduction of dysprosium content and develop simulation procedure for analysis of demagnetizations behaviours of interior and surface permanent magnet.

The purpose of this paper is to present a Preisach model to simulate the vector hysteresis properties of ferromagnetic materials.

The vector behavior has been studied at low frequency applying a single‐sheet tester with a round‐shaped specimen, and the locus of the magnetic flux density vector has been controlled by a digital measurement system. An inverse vector Preisach hysteresis model has been developed and identified by using the measured data.

Finally, the inverse model has been inserted into a finite element procedure through the combination of the fixed point technique and the reduced magnetic scalar potential formulation. The developed single‐sheet tester measurement system has been simulated. The applicability of the realized measurement system as well as the developed model has been proven by comparing measured and simulated results.

The identification technique is original, based on a previous work of the author.

The purpose of this paper is to implement and test a 1D eddy‐current model for laminated iron core of electrical machines and investigate the possibility of incorporating it in a 2D FE analysis.

The 1D eddy‐current model of laminated core is extended to handle rotating‐field problems and coupling between the x‐ and y‐components of the magnetic field. Explicit coupling terms are introduced in the Jacobean matrix to ensure convergence and time efficiency. The procedure is computationally tested for both the case where there is no feedback to the 2D FE and the case where the results of the eddy‐current model were fed‐back to the 2D analysis.

The coupling terms ensured fast and robust convergence. The incorporation of the eddy‐current model in the 2D FE analysis is possible, provided some under‐relaxation is used to ensure the convergence of the overall 1D‐2D procedure.

The method has been computationally tested with 2D like procedure corresponding to a 2D model with only one element. The behaviour of the model in actual 2D computation presents some problems related to the convergence of the overall procedure and they have been dealt with in another publication.

The paper is of practical value for designers of electrical machines. On one hand, the model can be used a posteriori to estimate eddy‐current losses in iron stacks, and on the other hand it can be incorporated into 2D FE analysis including the losses in the field solution and enhancing its power and energy balance.

The losses incurred in ferromagnetic materials under PWM excitations must be predicted accurately to optimize the design of modern electrical machines. The purpose of this paper is to employ mathematical hysteresis models (i.e. classical Preisach model) to predict iron losses in electrical steels under PWM excitation without compromising the computational complexity of the model.

In this paper, a novel approach based on the dynamic inverse Preisach model is proposed to model the iron losses. The PWM magnetic flux density waveform is decomposed into its harmonic component using Fourier series and a weighted Everett function is computed based on these harmonic components. The Preisach model is applied for the given flux waveform and results are validated against the measurements.

The paper predicts the total iron loss by computing a weighted Everett function based on the harmonics present in PWM waveform. Moreover, it formulates the possibility of utilizing the classical Preisach model to predict iron losses under PWM excitation.

The approach is still limited in terms of its application at high frequencies. This work may eventually lead toward the accurate prediction of iron loss under PWM excitation in electromagnetic machine design.

The paper provides a simple approach applying the Preisach model for the prediction of iron losses under PWM excitation. The proposed approach does not require additional experimental data beyond B-H loops measured under sinusoidal excitation.

A novel approach is presented to incorporate the frequency dependence into a static inverse Preisach model. The approach extends the ability of the static Preisach model to compute total iron loss under PWM excitation using a weighted Everett function.

A major purpose of vector hysteresis models lies in the prediction of power losses under rotating magnetic fields. The well-known vector Preisach model by Mayergoyz has been shown to well predict such power losses at low amplitudes of the applied field. However, in its original form, it fails to predict the reduction of rotational power losses at high fields. In recent years, two variants of a novel vector Preisach model based on rotational operators have been published and investigated with respect to general accuracy and performance. This paper aims to examine the capabilities of the named vector Preisach models in terms of rotational hysteresis loss calculations.

In a first step, both variants of the novel rotational operator-based vector Preisach model are tested with respect to their overall capability to prescribe rotational hysteresis losses. Hereby, the direct influence of the model-specific parameters onto the computable losses is investigated. Afterward, it is researched whether there exists an optimized set of parameters for these models that allows the matching of measured rotational hysteresis losses.

The theoretical investigations on the influence of the model-specific parameters onto the computable rotational hysteresis losses showed that such losses can be predicted in general and that a variation of these parameters allows to adapt the simulated loss curves in both shape and amplitude. Furthermore, an optimized parameter set for the prediction of the named losses could be retrieved by direct matching of simulated and measured loss curves.

Even though the practical applicability and the efficiency of the novel vector Preisach model based on rotational operators has been proven in previous publications, its capabilities to predict rotational hysteresis losses has not been researched so far. This publication does not only show the general possibility to compute such losses with help of the named vector Preisach models but also in addition provides a routine to derive an optimized parameter set, which allows an accurate modeling of actually measured loss curves.

The purpose of this paper is to implement the Anderson acceleration for different formulations of eletromagnetic nonlinear problems and analyze the method efficiency and strategies to obtain a fast convergence.

The paper is structured as follows: the general class of fixed point nonlinear problems is shown at first, highlighting the requirements for convergence. The acceleration method is then shown with the associated pseudo-code. Finally, the algorithm is tested on different formulations (finite element, finite element/boundary element) and material properties (nonlinear iron, hysteresis models for laminates). The results in terms of convergence and iterations required are compared to the non-accelerated case.

The Anderson acceleration provides accelerations up to 75 per cent in the test cases that have been analyzed. For the hysteresis test case, a restart technique is proven to be helpful in analogy to the restarted GMRES technique.

The acceleration that has been suggested in this paper is rarely adopted for the electromagnetic case (it is normally adopted in the electronic simulation case). The procedure is general and works with different magneto-quasi static formulations as shown in the paper. The obtained accelerations allow to reduce the number of iterations required up to 75 per cent in the benchmark cases. The method is also a good candidate in the hysteresis case, where normally the fixed point schemes are preferred to the Newton ones.

The purpose of this paper is to optimize the stator slot geometry of a high-speed electrical machine, which is used as an assist for a turbocharger. Meanwhile, the suitability of the Particle Swarm algorithm for such a problem is to be tested.

The starting point of the optimization is an existing design, for which the Particle Swarm algorithm is applied in conjunction with the transient time-stepping 2D finite element method.

It is found that regardless of its stochastic nature, the Particle Swarm work well for the optimization of electrical machines. The optimized design resulted in an increase of the slot area and increase of the iron loss, which was compensated by a dramatic decrease in the Joule losses.

The optimization was concentrated on the stator design whereas the rotor dimensioning was carried out withing the compressor and turbine design.

A turbocharger with electric assist is designed optimized and manufactured. The Particle Swarm algorithm is shown to be very stable.

The purpose of this paper is to present the application of the loss approximation method for non-oriented electrical steel developed by the authors. A new model of a toroidal sample with dimensions ensuring high uniformity of the field was presented.

A critical analysis of the methods used was carried out. Based on these considerations, the authors proposed their own loss approximation method, which allows obtaining high accuracy in a wide range of induction and frequency. The proposed method is based on the assumption that for a certain frequency range losses can be describe by two terms formula. For a fixed value of the peak flux density Bm, the graph of specific loss divided by the frequency should have the form of a straight line. Then, the obtained coefficients for different Bm are the basis for approximation with the power function.

The comparison of measurement and approximation results shows that the method allows to obtain very good accuracy in a wide range of induction and frequency.

More detailed studies on the impact of cutting on a larger number of samples with different geometrical dimensions are needed.

Application of the new method provides a better approximation of the curve of the loss and thus a more accurate calculation of the core loss in the electrical machines.

The paper presents the application of the loss approximation method for non-oriented electrical steel developed by the authors. A new model of a toroidal sample with dimensions ensuring high uniformity of the field was presented. It is shown that the approximation introduced allows for high accuracy in a wide range of frequency and magnetic flux density.

The purpose of this paper is to find out how uncertainties in the characterization of magnetic materials propagate through identification and numerical simulation to the computation of iron losses in electrical machines.

The probabilistic uncertainties in the iron losses are modelled with the spectral approach using chaos polynomials. The Sobol indices are used for the global sensitivity analysis. The machine is modelled with a 2D finite element method and the iron losses are computed with a previously developed accurate method.

The uncertainties propagate in different ways to the different components of losses, i.e. eddy current, hysteresis, and excess losses. The propagation is also different depending on the investigated region of the machine, i.e. Stator or rotor teeth, yokes, tooth tips.

The method does not account for uncertainties related to the manufacturing process, which might result in even larger variability.

A major implication of the findings is that the identification of iron loss parameters at low frequencies does not affect the loss variability. The identification with high-frequency measurement is very important for the rotor tooth tips. The variability in the excess loss parameters is of low impact.

The presented results are of importance for the magnetic material manufacturers and the electrical machine designers. The manufacturers can plan the measurement and identification procedures as to minimize the output variability of the parameters. The designers of the machine can use the result and the presented procedures to estimate the variability of their design.