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The purpose of this paper is to study the variation of the specific iron loss components of electrical steel sheets when applying a tensile mechanical load below the yield strength of the material. The results provide an insight into the iron loss behaviour of the laminated core of electrical machines which are exposed to mechanical stresses of diverse origins.

The specific iron losses of electrical steel sheets are measured using a standardised single-sheet tester equipped with a hydraulic pressure cylinder which enables application of a force to the specimen under test. Based on the measured data and a semi-physical description of specific iron losses, the stress-dependency of the iron loss components can be studied.

The results show a dependency of iron loss components on the applied mechanical stress. Especially for the non-linear loss component and high frequencies, a large variation is observed, while the excess loss component is not as sensitive to high mechanical stresses. Besides, it is shown that the stress-dependent iron loss prediction approximates the measured specific iron losses in an adequate way.

New applications such as high-speed traction drives in electric vehicles require a suitable design of the electrical machine. These applications require particular attention to the interaction between mechanical influences and magnetic behaviour of the machine. In this regard, knowledge about the relation between mechanical stress and magnetic properties of soft magnetic material is essential for an exact estimation of the machine’s behaviour.

This paper aims to use a scaling approach to scale the solutions of a beforehand-simulated finite element (FE) solution of an induction machine (IM). The scaling procedure is coupled to an analytic three-node-lumped parameter thermal network (LPTN) model enabling the possibility to adjust the machine losses in the simulation to the actual calculated temperature.

The proposed scaling procedure of IMs allows the possibility to scale the solutions, particularly the losses, of a beforehand-performed FE simulation owing to temperature changes and therefore enables the possibility of a very general multiphysics approach by coupling the FE simulation results of the IM to a thermal model in a very fast and efficient way. The thermal capacities and resistances of the three-node thermal network model are parameterized by analytical formulations and an optimization procedure. For the parameterization of the model, temperature measurements of the IM operated in the 30-min short-time mode are used.

This approach allows an efficient calculation of the machine temperature under consideration of temperature-dependent losses. Using the proposed scaling procedure, the time to simulate the thermal behavior of an IM in a continuous operation mode is less than 5 s. The scaling procedure of IMs enables a rapid calculation of the thermal behavior using FE simulation data.

The approach uses a scaling procedure for the FE solutions of IMs, which results in the possibility to weakly couple a finite element method model and a LPTN model in a very efficient way.

The calculation of electromagnetic fields can involve many degrees of freedom (DOFs) to achieve accurate results. The DOFs are directly related to the computational effort of the simulation. The effort is decreased by using the proper generalized decomposition (PGD) and proper orthogonalized decomposition (POD). The purpose of this study is to combine the advantages of both methods. Therefore, a hybrid enrichment strategy is proposed and applied to different electromagnetic formulations.

The POD is an a-priori method, which exploits the solution space by decomposing reference solutions of the field problem. The disadvantage of this method is given by the unknown number of solutions necessary to reconstruct an accurate field representation. The PGD is an a-priori approach, which does not rely on reference solutions, but require much more computational effort than the POD. A hybrid enrichment strategy is proposed, based on building a small POD model and using it as a starting point of the PGD enrichment process.

The hybrid enrichment process is able to accurately approximate the reference system with a smaller computational effort compared to POD and PGD models. The hybrid enrichment process can be combined with the magneto-dynamic T-Ω formulation and the magnetic vector potential formulation to solve eddy current or non-linear problems.

The PGD enrichment process is improved by exploiting a POD. A linear eddy current problem and a non-linear electrical machine simulation are analyzed in terms of accuracy and computational effort. Further the PGD-AV formulation is derived and compared to the PGD-T-Ω reduced order model.

This paper aims to compare different static history-independent hysteresis models (mathematical-, behavioural- and physical-based ones) and a history-dependent hysteresis model in terms of parameter identification effort and accuracy.

The discussed models were tested for distorted-excitation waveforms to explore their predictions of complex magnetization curves. Static hysteresis models were evaluated by comparing the calculated and measured major and minor static hysteresis loops.

The analysis shows that the resulting accuracy of the different hysteresis models is strongly dependent on the excitation waveform, i.e. smooth excitations, distorted flux waveforms, transients or steady-state regimes. Obtained results show significant differences between predictions of discussed static hysteresis models.

The general aim was to identify the models on a very basic and limited set of measured data, i.e. if possible using only the measured major static loop of the material. The quasi-static major hysteresis loop was measured at B_max = 1.5 T.

The presented analysis allows selection of the most-suited hysteresis model for the sought-for application and appraisal of the individual limitations.

The presented analysis shows differences in intrinsic mechanisms to predict magnetization curves of the majority of the well-known static hysteresis models. The results are essential when selecting the most-suited hysteresis model for a specific application.

Due to the increasing amount of high power density high-speed electrical machines, a detailed understanding of the consequences for the machine’s operational behaviour and efficiency is necessary. Magnetic materials are prone to mechanical stress. Therefore, this paper aims to study the relation between the local mechanical stress distribution and magnetic properties such as magnetic flux density and iron losses.

In this paper, different approaches for equivalent mechanical stress criteria are analysed with focus on their applicability in electrical machines. Resulting machine characteristics such as magnetic flux density distribution or iron are compared.

The study shows a strong influence on the magnetic flux density distribution when considering the magneto-elastic effect for all analysed models. The influence on the iron loss is smaller due to a high amount of stress-independent eddy current loss component.

The understanding of the influence of mechanical stress on dimensions of electrical machines is important to obtain an accurate machine design. In this paper, the discussion on different equivalent stress approaches allows a new perspective for considering the magneto-elastic effect.

Magnetic properties of electrical steel are affected by mechanical stress. In electrical machines, influences because of manufacturing and assembling and because of operation cause a mechanical stress distribution inside the steel lamination. The purpose of this study is to analyse the local mechanical stress distribution and its consequences for the magnetic properties which must be considered when designing electrical machines.

In this paper, an approach for modelling stress-dependent magnetic material properties such as magnetic flux density using a continuous local material model is presented.

The presented model shows a good approximation to measurement results for mechanical tensile stress up to 100 MPa for the studied material.

The presented model allows a simple determination of model parameters by using stress-dependent magnetic material measurements. The model can also be used to determine a scalar mechanical stress distribution by using a known magnetic flux density distribution.

The goal of this research is to investigate the convergence behavior of the Newton iteration, when solving the nonlinear problem with consideration of hysteresis effects. Incorporating the vector hysteresis model in the magnetic vector potential formulation has encountered difficulties. One of the reasons is that the Newton method is very sensitive regarding the starting point and states distinct requirements for the nonlinear function in terms of monotony and smoothness. The other reason is that the differential reluctivity tensor of the material model is discontinuous due to the properties of the stop operators. In this work, line search methods to overcome these difficulties are discussed.

To stabilize the Newton iteration, line search methods are studied. The first method computes an error-oriented search direction. The second method is based on the Wolfe-Powell rule using the Armijo condition and curvature condition.

In this paper, the differentiation of the vector stop model, used to evaluate the Jacobian matrix, is studied. Different methods are applied for this nonlinear problem to ensure reliable and stable finite element simulations with consideration of vector hysteresis effects.

In this paper, two different line search Newton methods are applied to solve the magnetic field problems with consideration of vector hysteresis effects and ensure a stable convergence successfully. A comparison of these two methods in terms of robustness and efficiency is presented.

Traction applications, e.g. the IMs are mainly operated by field-oriented control (FOC). This control technique requires an accurate knowledge of the machine’s parameters, such as the main inductance, the leakage inductances and the stator and rotor resistance. The accuracy of the parameters influences the precision of the calculated rotor flux and the rotor flux angle and the decoupling of the machine’s equations into the direct and quadrature coordinate system (dq-components). Furthermore, the parameters are used to configure the controllers of the FOC system and therefore influence the dynamic behavior and stability of the control.

In this paper, three different methods to calculate the machine’s parameters, in an automated and rapid procedure with minimal measuring expenditure, are analyzed and compared. Moreover, a method to configure a control that reduces the overall Ohmic losses of the machine in every torque speed operation point is presented. The machine control is configured only with the identified machine parameter.

Simulations and test bench measurements show that the evolutionary strategy is able to identify the electrical parameters of the machine in less time and with low error. Moreover, the controller is able to control the torque of the machine with a deviation of less than 2 per cent.

The most significant contribution of the research is the potential to identify the machine parameter of an induction motor and to configure an accurate control with these parameters.