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Small highly saturated interior permanent magnet- synchronous machines (IPMSMs) show a very nonlinear behaviour. Such machines are mostly controlled with a closed-loop cascade control, which is based on a d-q two-axis dynamic model with constant concentrated parameters to calculate the control parameters. This paper aims to present the identification of a complete current- and rotor position-dependent d-q dynamic model, which is derived by using a finite element method (FEM) simulation. The machine’s constant parameters are determined for an operation on the maximum torque per ampere (MTPA) curve. The obtained MTPA control performance was evaluated on the complete FEM-based nonlinear d-q model.

A FEM model was used to determine the nonlinear properties of the complete d-q dynamic model of the IPMSM. Furthermore, a fitting procedure based on the nonlinear MTPA curve is proposed to determine adequate constant parameters for MTPA operation of the IPMSM.

The current-dependent d-q dynamic model of the machine models the relevant dynamic behaviour of the complete current- and rotor position-dependent FEM-based d-q dynamic model. The most adequate control response was achieved while using the constant parameters fitted to the nonlinear MTPA curve by using the proposed method.

The effect on the motor’s steady-state and dynamic behaviour of differently complex d-q dynamic models was evaluated. A workflow to obtain constant set of parameters for the decoupled operation in the MTPA region was developed and their effect on the control response was analysed.

This paper presents a comparative study of different stator-segmentation topologies of a permanent magnet synchronous machine (PMSM) used in traction drives and their effect on iron losses. Using stator segmentation allows one to achieve more significant copper fill factors, resulting in increased power densities and efficiencies. The segmentation of the stators creates additional air gaps and changes the soft magnetic material’s material properties due to the cut edge effect. The aim of this paper is to present an in-depth analysis of the influence of stator segmentation on iron losses. The main goal was to compare various segmentation methods under equal excitation conditions in terms of their influence on iron loss.

A transient finite element method analysis combined with an extended iron-loss model was used to evaluate discussed effects on the stator’s iron losses. The workflow to obtain a homogenized airgap length accounting for cut edge effects was established.

The paper concludes that the segmentation in most cases slightly decreases the iron losses in the stator because of the overall reduced magnetic flux density B due to the additional air gaps in the magnetic circuit. An increase of the individual components, as well as total power loss, was observed in the Pole Chain segmentation design. In general, segmentation did not change the total iron losses significantly. However, different segmentation methods resulted in the different distortion of the magnetic field and, consequently, in different iron loss compositions. The analysed segmentation methods exhibited different iron loss behaviour with respect to the operation points of the machine. The final finding is that analysed stator segmentations had a negligible influence on the total iron loss. Therefore, applying segmentation is an adequate measure to improve PMSMs as it enables, e.g. increase of the winding fill factor or simplifying the assembly processes, etc.

The influence of stator segmentation on iron losses was analysed. An in-depth evaluation was performed to determine how the discussed changes influence the individual iron loss components. A workflow was developed to achieve a computationally cheap homogenized 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.

This paper aims to present two hysteresis-control algorithms designed for medium-frequency, direct-current, resistance-spot-welding (MFDC RSW) systems. The first proposed control algorithm (MSCHC) eliminates the short switching cycles that can occur when using the existing hysteresis-control algorithms. This control minimises the number of switching cycles that are needed to generate the selected welding current. The welding-current ripple can be high when using this control algorithm. Therefore, a second algorithm (HCRR) is presented that reduces the welding-current ripple by half.

The proposed hysteresis controllers consist of the transformer’s magnetic-flux-density hysteresis regulator and a welding-current hysteresis regulator. Therefore, the welding current must be measured and the saturation of the iron core must be detected. The proposed hysteresis controller supplies the inverter with the signals needed to generate the supply voltage for the RSW transformer, which then generates the selected welding current.

The proposed MSCHC algorithm produces the smallest possible number of switching cycles needed to generate the selected welding current. The high welding-current ripple can be reduced if the number of switching cycles is increased. The observed number of switching cycles and the welding-current ripple change if the welding resistance and/or inductance change.

The number of switching cycles can be minimised when using the first proposed control algorithm (MSCHC), and so the switching power losses can be minimised. If the welding-current ripple produced by the first control algorithm is unacceptable, the second control algorithm (HCRR) can reduce it by increasing the number of switching cycles.

The purpose of this paper is to provide a comprehensive analysis of different material models when observing the magnetisation dynamics and power losses in non-oriented soft magnetic steel sheets (SMSSs).

During the analysis four different magnetic material models were used for describing the static material characteristics, which characterised the materials’ magnetisation behaviour with increasing accuracies: linear material model, piecewise linear material model, non-linear H(B) characteristic and the static hysteresis material model proposed by Tellinen. The described material models were implemented within a parametric magneto-dynamic model (PMD) of SMSSs, where the dynamic responses as well as power loss calculations from the obtained models were analysed.

The momentous influences of various levels of detail on the calculation of dynamic variables and power losses inside SMSS with non-uniform magnetic fields were elaborated, where various static material characteristic models were evaluated, ranging from linear to hysteretic constitutive relationships.

The resulting PMD model using different static models was analysed over a frequency range from quasi-static to f=1,000 Hz for different levels of magnetic flux density up to B _max=1.5 T.

The presented analysis provides fundamental insight when calculating dynamic electromagnetic variables and power losses inside non-linear SMSSs, which is instrumental when selecting an adequate model for a specific application.

This paper provides closer insight on the way non-linearity, magnetic saturation and hysteresis affect the energy loss and magnetisation dynamics in SMSSs through the level of detail in the used material model. The strongly coupled model addresses both induced eddy currents and the ferromagnetic materials’ magnetisation behaviour simultaneously using varying levels of detail so that the interplay between skin effect (i.e. eddy currents) across laminations and hysteresis can be resolved accurately. Therewith, adequate models for specific applications can be selected.

The aim of the paper is to provide a simple and reliable hysteresis model for prediction of magnetization curves of a resistance spot welding transformer (RSWT) core, operating in a wide range of flux densities and excitation frequencies.

The hysteresis model considered in the paper is the T(x) description advanced by J. Takács. Three options to extend the model to the dynamic magnetization conditions are considered. The excitation conditions differ from those prescribed by international standards.

The quasi‐static Takács model combined with a fractional viscosity equation similar to that proposed by S.E. Zirka outperforms other considered options. The effect of eddy currents may be considered as a disturbance factor to the frequency‐independent quasi‐static hysteresis loop.

The combined approach yields in most cases a satisfactory agreement between theory and experiment. For highest frequency considered in the paper (1 kHz) excessive “heels” were observed in the modelled loops. This artifact may be reduced by the introduction of a more complicated relationship for the viscous term. Future work shall be devoted to this issue.

The combined Takács‐Zirka model is a useful tool for prediction of magnetization curves of a RSWT core in a wide range of flux densities and excitation frequencies.

The usefulness of the Takács description has been verified in a practical application. The model is able to predict magnetization curves under non‐standard excitation conditions.

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.

We investigated the effectiveness of using feature films in teaching organizational behavior courses at the undergraduate level at a mid-Western university in the USA.

Our model included the impact of film analysis on self-perceived learning outcomes and cognitive and affective changes among students. Structural equation modeling using partial least squares and contemporary mediation analysis techniques were employed.

Featured film analysis positively impacted perceived learning outcomes and the cognitive and affective components of learning among students. We also found an indirect effect on cognitive and affective change, indicating that learners’ improved perceived learning outcomes deepened their learning and resulted in greater appreciation of organizational behavior theories.

Films are effective pedagogical tools for teaching complex business theories and principles. We recommend that faculty members pay careful attention to selecting films for study and should design film analysis projects aligned with meaningful course learning outcomes. Appropriate films and carefully designed learning outcomes trigger cognitive changes and have a lasting influence on students beyond the semester.

Our study is one of the few empirical studies demonstrating the effectiveness of feature films as a pedagogical tool for organizational behavior courses.

To assess which partnerships were most critical during the recovery planning process following Hurricanes Maria and Irma. We discuss the roles and impact of different types of partners, barriers and facilitators to partnerships and lessons in collaboration during the development of the economic and disaster recovery plan for Puerto Rico.

The Homeland Security Operational Analysis Center (HSOAC) was tasked with assisting the Puerto Rican government with an assessment of damages from Hurricanes Maria and Irma and the development of the Recovery Plan. During the process, a small team compiled and coded a database of meetings with non-HSOAC partners. The team was divided into sector teams that mirrored FEMA’s Recovery Support Functions. Each sector completed two surveys identifying high impact partners and their roles and contributions, as well as barriers and facilitators to partnerships.

A total of 1,382 engagements were recorded across all sectors over seven months. The most frequently identified high impact partners were federal and Puerto Rican governmental organizations partners. NGOs and nonprofits were noted as key partners in obtaining community perspective. Sector teams cited a lack of trust and difficulty identifying partners as barriers to partner engagement. Given the expedited nature of disaster response, establishing partnerships before disasters occur may help facilitate community input. Early networking, increased transparency and defining roles and responsibilities may increase trust and effectiveness among partnerships.

To our knowledge, this is one of the few studies that quantifies and illustrates the partnerships formed and their contributions during recovery planning, and lessons learned.