Losses In Electrical Machines Research Articles

Neural network‐based simulation of fields and losses in electrical machines with ferromagnetic laminated cores

AbstractDue to the distribution of eddy currents inside ferromagnetic laminations, the accurate modeling of magnetic fields and losses in the laminated cores of electrical machines requires resolving individual laminations with a fine 3D discretization. This yields finite element models so huge and costly that they are unusable in daily industrial R&D. In consequence, hysteresis and eddy currents in laminations are often simply disregarded in the modeling: the laminated core is assumed to be made of a reversible (non lossy) saturable material, and magnetic losses are evaluated a posteriori, by means of Steinmetz–Bertotti like empirical formulas. However, in a context where industry is struggling to minutely assess the impact of magnetic losses on their devices, this simplified approach is more and more regarded as inaccurate and unsatisfactory. This article proposes a solution to this issue, based on homogenization and on detailed mesoscopic simulations of eddy currents and hysteresis inside the laminations. The proposed approach results in a close‐to‐conventional 2D magnetic vector potential finite element model, but equipped with an irreversible parametric material law to represent the ferromagnetic stack. In each finite element, the parameters of the law are obtained from a neural network trained to best fit the detailed mesoscopic simulations of the laminations subjected to the same local magnetic field. This way, all aspects of the irreversible ferromagnetic response are appropriately accounted for in the finite element simulation, but at a computational cost drastically reduced with regard to a brute force 3D calculation, and comparable to that of conventional 2D finite element simulations.

Carbon Nanotubes as an Alternative to Copper Wires in Electrical Machines: A Review

The surge in electric vehicles (EVs) and their electrical appliances requires highly efficient, lightweight electrical machines with better performance. However, conventional wire used for electrical machine windings have certain limits to the current requirements. Copper is a commonly used material in electrical windings, and due to its ohmic resistance, it causes 75% of total losses in electrical machines (copper losses). The high mass of the copper results in a bulky system size, and the winding temperature of copper is always maintained at less than 150 °C to preserve the thermal insulation of the electric machine of the windings. On the other hand, carbon nanotubes and carbon nanotube materials have superior electrical conductivity properties and mechanical properties. Carbon nanotubes ensure 100 MS/m of electrical conductivity, which is higher than the copper electrical conductivity of 59.6 MS/m. In the literature, various carbon nanotubes have been studied based on electrical conductivity, temperature co-efficient with resistivity, material thickness and strength, insulation, and efficiency of the materials. Here, we review the electrical and mechanical properties of carbon nanotubes, and carbon nanotube composite materials are reviewed with copper windings for electrical wires.

Investigation of Rotational Magnetization Under Non-Sinusoidal Excitation for Non-Oriented Material

Rotational loss forms a significant portion of total core losses in electrical machines. The influence of harmonics on the behavior of magnetic materials is inevitable as these machines are mostly supplied by power electronic converters. Minor loops in hysteresis curves due to harmonics lead to additional losses. While the case of alternating induction (1-D magnetization) with harmonics is thoroughly considered in the literature, the assessment of the effect of rotational magnetization (2-D magnetization) has not yet been done adequately. A qualitative evaluation of rotational hysteresis loops in the presence of minor loops is carried out. The impact of minor loops in the evolution of hysteresis loops under rotating fields is examined. A peculiar behavior of interleaving of hysteresis loops under rotational magnetization is observed, which will affect the total core loss. This analysis can be used to visualize flux patterns on account of rotational magnetization and to accurately predict the performance of a machine during its predesign stage.

New formulation of Loss-Surface Model for accurate iron loss modeling at extreme flux density and flux variation: Experimental analysis and test on a high-speed PMSM

The Loss-Surface (LS) model, commonly used for the prediction of iron losses in electrical machines, is reformulated for better accuracy and reliability when it is extrapolated beyond the parametric identification region. First, the dynamic hysteresis behaviors of typical soft magnetic materials are analyzed by both measurements and FE simulations. They are then described by the LS model using different mathematical formulations. The most relevant one, which requires 14 parameters to reproduce and extrapolate any loss surface, will be presented in this paper. The newly reformulated LS model is tested, in the last part, to estimate the iron losses of intrinsic measurements as well as of an electrical machine. In the first case, the results obtained of four different materials are generally within 5% error. And in the latter case of a high speed permanent magnet synchronous motor, by performing a study on the effects of manufacturing methods (punching and assemble) with respect to the iron losses, it is shown that the LS model provides an estimation with around 10% of deviation.

Analysis and Mitigation of AC Losses in High Performance Propulsion Motors

In this paper, the AC copper losses in classical random windings are investigated and mitigated using several techniques across a range of permanent magnet synchronous motor designs. At high operating frequencies, AC copper losses can represent a substantial share of the total loss in electrical machines, thus, reducing the machine’s overall performance, and increasing the thermal loading. Recently, different approaches for modelling AC copper losses have been proposed. This paper utilises simulation software to quantify the expected AC losses in six different propulsion motor designs. The motor designs are then modified to reduce the AC winding losses through the implementation of five different methods. Using two-dimensional finite element analysis, the magnetisation direction, magnet to airgap ratio, copper stranding, magnetic wedges and the motor slot openings are modified to reduce AC losses. The paper considers distributed, fractional, slot and concentrated windings, and the results show promising reductions across these different winding configurations.

Minimization of Winding AC Losses Using Inhomogeneous Electrical Conductivity Enabled by Additive Manufacturing

The electrical conductivity (EC) of additively manufactured conductors can be purposely controlled by changing as-built orientation and postprocessing conditions. This feature can be leveraged to minimize winding alternate current (ac) losses in electrical machines adopting solid conductors. This article deals with the additive-manufacturing-based winding design of a high-specific-power permanent-magnet (PM) machine for aerospace applications. Specifically, conductors near slot opening are designed with low EC to reduce winding AC losses, while conductors near slot bottom adopt higher EC to reduce direct current (DC) losses. Parametric finite element models are developed for a thorough design parametric analysis targeting high-specific power as well as high efficiency. The implementation of the proposed coil concept with inhomogeneous EC is discussed and demonstrated. The EC measurements on rod and coil samples are conducted for material characterization.

Losses in Efficiency Maps of Electric Vehicles: An Overview

In some applications such as electric vehicles, electric motors should operate in a wide torque and speed ranges. An efficiency map is the contour plot of the maximum efficiency of an electric machine in torque-speed plane. It is used to provide an overview on the performance of an electric machine when operates in different operating points. The electric machine losses in different torque and speed operating points play a prominent role in the efficiency of the machines. In this paper, an overview about the change of various loss components in torque-speed envelope of the electric machines is rendered to show the role and significance of each loss component in a wide range of torque and speeds. The research gaps and future research subjects based on the conducted review are reported. The role and possibility of the utilization of the computational intelligence-based modeling of the losses in improvement of the loss estimation is discussed.

New Investigations in Play Static Hysteresis Model for Increased Accuracy and Robustness

This article presents an evolution of the inverse Play model to reconstruct static hysteresis from a flux density waveform input. It is to be combined with dynamic and 2-D or 3-D models to estimate the complete iron loss in electrical machines. In the first part of the article, the article shows the significant improvement in the original inverse Play model accuracy obtained by modifying the characterization measurement methodology, the subsequent discretization, and the identification method. Thereafter, a new version of the Play model, named “continuous,” is introduced, which allowed a significant gain in performance at the expense of greater computation time for the identification process. Both model versions have been validated through experimental comparison. All measurements, characterization, and validation have been done according to IEC60404-2 on two different test laboratories. The studied material is non-oriented SiFe M400-50A electrical steel.

Effects of Manufacturing Processes on Core Losses of Electrical Machines

Manufacturing processes such as cutting, welding and shrink fitting are known to degrade the magnetic properties of the electrical sheet during the manufacturing of electrical machines. These effects are often neglected at the design stage and lead to large errors in the simulated and measured core losses of the electrical machine. This article studies the comparative impact of different manufacturing processes on the stator core losses of a typical industrial motor. Both simulations and measurements indicate a significant impact of manufacturing processes on the stator core losses. A dummy blocked rotor test setup is used to measure the stator core losses. As a result of different manufacturing processes, the stator core losses increased by 23% in the studied machine at the rated condition. The effect on the stator core losses was higher at lower flux levels. Finally, it was shown that the inclusion of the effect of manufacturing processes significantly improved the simulation accuracy of the core losses. A quantification and segregation of the effect of cutting, welding and shrink fitting is also presented for the studied machine.

Iron Loss Modelling of Electrical Traction Motors for Improved Prediction of Higher Harmonic Losses

A Finite Element (FE) modelling approach is presented to account for the core losses in electrical machines that are generated by higher harmonic frequencies, for example those caused by Pulse Width Modulation (PWM) switching or by space harmonics due to the machine geometry. The model builds further on a post-processing calculation tool that was recently developed to take into account the magnetic skin effect in electrical steel laminations at high frequencies, and extends this by a more detailed loss analysis of the minor hysteresis loops that are caused by the higher harmonics. Further, these tools for high-frequency loss analysis are integrated into a complete electrical machine model with separate consideration of the major and minor loops. The modelling approach relies strongly on extensive magnetic measurement data of the electrical steel, in order to accurately predict the different loss components for minor hysteresis loops as a function of the DC bias field, frequency and amplitude of the minor loop. Results from the model are shown for an automotive traction motor, illustrating the losses caused by PWM harmonics and demonstrating the relevance of including the skin effect in these calculations.

Additive Manufacturing of Shaped Profile Windings for Minimal AC Loss in Electrical Machines

Metal additive manufacturing enables production of copper and aluminium parts exhibiting unmatched geometric freedom, giving rise to new possibilities in the winding design of electrical machines and wound passive components. Early adopters of additive manufacturing are primarily concerned with improving power-density or efficiency by increasing slot fill-factor, optimizing end-winding topology or incorporating cooling channels into the conductors. In this article, a method of minimizing the elevated ac loss present in open slot electrical machine topologies is presented, in which individual conductor profiles are shaped according to their magnetic environment. Such shaped profile windings are shown to exhibit operating mode dependent loss behavior giving them potential for efficiency improvement in applications with a dominant operating mode such as electric vehicle traction, aerospace propulsion fans, and generators. For the first time, the conductor shaping method and associated benefits are demonstrated by the retrospective design, additive manufacture, and experimental test of a three-phase set of shaped profile windings for a concentrated wound, open slot, permanent magnet electrical machine.

An Accurate Iron Core Loss Model in Equivalent Circuit of Induction Machines

Iron core loss is the major loss in electrical machines. It performs up to 25% of total machine losses. The machine efficiency calculation requires an accurate prediction of losses. The accuracy of losses calculation depends largely on the equivalent circuit parameter determination and measurements. In this paper, an accurate procedure of iron core loss determination considering the variation effect of supply voltage, iron core temperature, rotor parameters due to skin effect, and magnetizing saturation. The iron core resistance is performed as main component in the equivalent circuit. This resistance is a function of supply voltage and used to calculate part of stray loss as well as iron core loss. The theoretical model is compared with practical results with high accuracy, which proves the validity of the proposed procedure.

Iron-Loss and Magnetization Dynamics in Non-Oriented Electrical Steel: 1-D Excitations Up to High Frequencies

This paper presents a thorough introduction to and application of the Parametric Magneto-Dynamic (PMD) model of soft magnetic steel sheets. The theoretical background is reviewed, and two different ways are discussed to account for the viscosity-like effects originating from microscopic eddy currents. This is followed by the theoretical calculation of magnetization dynamics and dynamic hysteresis loops in Non-Oriented (NO) electrical steel. Both classical and viscosity-extended approaches are discussed, with respect to the ability of replicating the dynamic hysteresis loop shape and iron-loss under sinusoidal excitation waveforms up to high excitation frequencies. Comparisons against measurements are analyzed for M400-50A and M235-35A NO electrical steel over a wide range of magnetic flux density and excitation frequencies. The proven accuracy and efficiency of the PMD model make it a valuable tool for the calculation of iron losses in electrical machines and transformers, as well as for an in-depth study of magnetization dynamics in individual laminations.

Energy loss prediction in nonoriented materials using machine learning techniques: A novel approach

AbstractTraditional extrapolation performed by machine designers for energy loss estimation results in the decrease of the overall efficiency of electrical machines. Therefore, state‐of‐the‐art techniques need to be developed in order to accurately predict the energy loss in electrical machines for their improved performance. To this end, machine learning techniques have been employed to predict accurate energy loss at different frequencies and induction levels under rotational conditions. Such types of flux exist near the teeth of the stator in synchronous machines. In transformers, rotational flux arises at the bends and corners of the stators. It was observed that the random forest machine learning algorithm has the least mean square error and as such is the most suited algorithm, which can be used for the accurate prediction of energy loss in nonoriented materials.

Effect of Laser Cutting on Core Losses in Electrical Machines—Measurements and Modeling

Cutting of the electrical steel sheets to appropriate shape and size is performed during the manufacturing of electrical machines that leads to the magnetic material deterioration near the cutting edge. Epstein frame measurements of electrical steel samples of different widths cut by laser cutting are carried out in the range of 20–400 Hz frequency of sinusoidal excitations. Two stators one with laser cut and another one with electric discharge wire cutting are manufactured and the effect of cutting on core losses is analyzed. The effect of cutting on the magnetic permeability and core losses are modeled with analytical equations. Furthermore, the model is implemented in the finite-element (FE) simulation of the Epstein frame test setup. The presented loss model is found to reproduce the measurement results reasonably. The loss model is then applied to the simulation of a cage induction machine with time-stepping FE analysis (FEA). A significant increase in core losses was observed both in simulations and measurements due to the effect of laser cutting. The presented cutting model closely follows the measured core losses.

Sensitivity Analysis of Inverse Thermal Modeling to Determine Power Losses in Electrical Machines

Inverse analysis is a known mathematical approach, which has been used to solve physical problems of a particular nature. Nevertheless, it has seldom been applied directly for loss reconstruction of electrical machines. This paper aims to verify the accuracy of an inverse methodology used in mapping power loss distribution in an induction motor. Conjugate gradient method is used to iteratively find the unique inverse solution when simulated temperature measurement data are available. Realistic measurement situations are considered and the measurement errors corresponding to thermographic measurements and temperature sensor measurements are used to generate simulated numerical measurement data. An accurate 2-D finite-element thermal model of a 37 kW cage induction motor serves as the forward solution. The inverse model’s objective is to map the power loss density in the motor accurately from noisy temperature measurements made on the motor housing’s outer surface. Furthermore, the sensitivity of the adopted inverse methodology to variations in the number of available measurements is also considered. Filtering the applied noise to acceptable ranges is shown to improve the inverse mapping results.

Research on windage losses of smooth rotor supported by active magnetic bearings in a vacuum chamber

In order to study the windage losses caused by the friction between fluid and rotor surface in high speed rotating machines, a series of rundown experiments are performed in a vacuum chamber. By means of an evacuation method, the windage losses are extracted by subtraction operation between specified pressure and near absolute vacuum. The windage losses separated with existing separation models for large gap are compared to the extracted values with evacuation method and the results show big disagreements. For this reason, a modified separation model considering the skin effect and gas state is presented for rotating electrical machines simultaneously including both large and small gap. Using the modified separation model, the results show good agreements with the extracted values. In contrast to the evacuation method, the new model provides a way to quickly assess windage losses in electrical machines, where vacuuming is not obligatory any more.

Additional Losses of Electrical Machines Under Torsional Vibration

Electric drive trains have a torsional rigid-body vibration mode at a small, nonzero frequency. If an excitation occurs close to this frequency, the vibration amplitude may grow large and the electrical machine may suffer from significant additional losses. Standards set constraints on the oscillating torque in the shaft coupling and on the harmonics of line current. They indirectly limit the vibration amplitude and losses of the machines. Time-discretized finite-element analysis was used to study the losses of six induction and six synchronous machines under torsional vibration restricted by the constraints above. All the machines were supplied from sinusoidal voltage sources. In the worst cases of the induction motors, the vibration increased the electromagnetic total loss by about 20%. The constraints on synchronous machines are milder than those for induction machines. In this case, the maximum increase of the loss was 75%. The limit on the harmonic currents is essential from the loss point of view. Without this limit, the additional loss at the rigid-body resonance would lead to a temperature rise high enough to destroy the insulation system of the machine. The method of loss analysis was validated by measured results.

Losses analysis of soft magnetic ring core under sinusoidal pulse width modulation (SPWM) and space vector pulse width modulation (SVPWM) excitations

Practical core losses in electrical machines differ significantly from those experimental results using the standardized measurement method, i.e. Epstein Frame method. In order to obtain a better approximation of the losses in an electrical machine, a simulation method considering sinusoidal pulse width modulation (SPWM) and space vector pulse width modulation (SVPWM) waveforms is proposed. The influence of the pulse width modulation (PWM) parameters on the harmonic components in SPWM and SVPWM is discussed by fast Fourier transform (FFT). Three-level SPWM and SVPWM are analyzed and compared both by simulation and experiment. The core losses of several ring samples magnetized by SPWM, SVPWM and sinusoidal alternating current (AC) are obtained. In addition, the temperature rise of the samples under SPWM, sinusoidal excitation are analyzed and compared.

A New Iron Loss Model for Temperature Dependencies of Hysteresis and Eddy Current Losses in Electrical Machines

In this paper, the different temperature dependencies of hysteresis and eddy current losses of non-oriented Si-steel laminations are investigated. The measured iron loss results show that both the hysteresis and eddy current losses vary linearly with temperature between 40 °C to 100 °C, a typical temperature range of electrical machines. Varying rates of hysteresis and eddy current losses with the temperature are different and fluctuate with flux density and frequency. Based on this, an improved iron loss model which can consider temperature dependencies of hysteresis and eddy current losses separately is developed. Based on the improved iron loss model, the temperature influence on the iron loss can be fully considered by measuring iron losses at only two different temperatures. The investigation is experimentally validated by both the tests based on a ring specimen and an electrical machine.