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Due to the rise of e-mobility applications, there is an increased demand to create more accurate control methods, which can reduce the loss in an e-drive system. The accurate modeling of the rotating machines needs to resolve a partial differential equation system that describes the thermal and mechanical behavior of the different parts in addition to the electromagnetic design. Due to these models' limited resources and high computation demand, they cannot be used directly for real-time control. Model order reduction methods have been of growing interest in the past decades and offer solutions for this problem. According to the processed literature, many model order reduction-based methods are used for a wide range of problems. However, a paper has not been published that discusses a model order reduction-based real-time control model that is actually used in the industry. This paper aims to summarize and systematically review the model order reduction methods developed for rotating electrical machines in the last two decades and examine the possible usage of these methods for a real-time control problem. [ABSTRACT FROM AUTHOR]

Induction heating is a clear, cheap, and highly effective technology used for many industrial and commercial applications. Generally, a time-varying magnetic field produces the required heat in the workpiece with a specially designed coil. The efficiency of the heating process depends highly on the coil design and the geometrical arrangement. A detailed and accurate finite element analysis of the induction heating process usually needs to resolve a coupled thermoelastic–magnetic problem, whose parameters values depend on the solution of another field. The paper deals with a shrink-fitting process design problem: a gear should be assembled with an axe. The interesting part of this case study is given the prescribed low limits for critical stress, the temperature of the gear material, and the heat-treated wearing surfaces. A coupled finite-element-based model and a genetic algorithm-based parameter determination methodology were presented. A thermal imaging-based measurement validated the presented numerical model and parameter determination task. The results show that the proposed methodology can be used to calibrate and validate the numerical model and optimize an induction heating process. [ABSTRACT FROM AUTHOR]

Innovative technological solutions have become increasingly critical in addressing the transportation sector's environmental impact. Passenger vehicles present an opportunity to introduce novel drivetrain solutions that can quickly penetrate the electric vehicle market due to their shorter development time and lifetime compared to commercial vehicles. As environmental policy pressure increases and customers demand more sustainable products, shifting from a linear business approach to a circular economy model is in prospect. The new generation of economically competitive machines must be designed with a restorative intention, considering future reuse, refurbishment, remanufacture, and recycling possibilities. This review investigates the market penetration possibilities of permanent magnet-assisted synchronous reluctance machines for mini and small-segment electric vehicles, considering the urban environment and sustainability aspects of the circular economy model. When making changes to the materials used in an electric machine, it is crucial to evaluate their potential impact on efficiency while keeping the environmental impact of those materials in mind. The indirect ecological effect of the vehicle's use phase may outweigh the reduction in manufacturing and recycling at its end-of-life. Therefore, thoroughly analysing the materials used in the design process is necessary to ensure maximum efficiency while minimising the environmental impact. [ABSTRACT FROM AUTHOR]

The installed solar capacity in the European Union has expanded rapidly in recent years. The production of these plants is stochastic and highly dependent on the weather. However, many factors should be considered together to estimate the expected output according to the weather forecast so that these new PV plants can operate at maximum capacity. Plants must be operated in coordination with maintenance operations and considering actual energy market prices. Various methods have recently been developed in the literature, ranging from the most impactful artificial-intelligence-based generation estimation methods to various diagnostic and maintenance methods. Moreover, the optimal operational and maintenance strategy usually depends on market regulation, and there are many concerns related to the distribution system operator. This review article aims to summarize and illustrate the challenges of operating and maintaining solar power plants and the economic and technical importance of these problems. [ABSTRACT FROM AUTHOR]

Three-dimensional printing is a promising technology that offers increased freedom to create topologically optimised electrical machine designs with a much smaller layer thickness achievable with the current, laminated steel-sheet-based technology. These composite materials have promising magnetic behaviour, which can be competitive with the current magnetic materials. Accurately calculating the iron losses is challenging due to magnetic steels' highly nonlinear hysteretic behaviour. Many numerical methodologies have been developed and applied in FEM-based simulations from the first introduced Steinmetz formulae. However, these old curve-fitting-based iron loss models are still actively used in modern finite-element solvers due to their simplicity and high computational demand for more-accurate mathematical methods, such as Preisach- or Jiles–Atherton-model-based calculations. In the case of 3D-printed electrical machines, where the printed material can have a strongly anisotropic behaviour and it is hard to define a standardised measurement, the applicability of the curve-fitting-based iron loss methodologies is limited. The following paper proposes an overview of the current problems and solutions for iron loss calculation and measurement methodologies and discusses their applicability in designing and optimising 3D-printed electrical machines. [ABSTRACT FROM AUTHOR]

The accurate measurement and modeling of ferromagnetic material losses are vital issues during the design and analysis of electrical machines. Higher loss values can describe the manufactured rotor and stator machine plates better than the catalog data obtained by standardized measurements using the Epstein frame. In this paper, different temperature-dependent models based on the loss-separation principle are introduced and compared with the measurements. The model parameters are computed from customized laboratory and standardized measurements. The customized measurements based on the stator part of an induction machine in the range of the automotive industry standard, i.e., in [−40 ° C, ⋯, 180 ° C]. The proposed model and measurement process can be used in the post-processing stage of numerical field analysis to obtain electromagnetic losses according to the agreement between measured and simulated results. During a numerically expensive optimization process, this model can be used to consider the temperature dependence of the losses more accurately. The study shows that more than 50% of loss increase can be measured, compared with the catalog data, if we use the manufactured, stator-based, customized measurements based on the estimation of the iron loss parameters. [ABSTRACT FROM AUTHOR]

There were many promising superconducting materials discovered in the last decades that can significantly increase the efficiency of large power transformers. However, these large machines are generally custom-made and tailored to the given application. During the design process the most economical design should be selected from thousands of applicable solutions in a short design period. Due to the nonlinearity of the task, the cost-optimal transformer design, which has the smallest costs during the transformers' planned lifetime, is usually not the design with the highest efficiency. Due to the topic's importance, many simplified transformer models were published in the literature to resolve this problem. However, only a few papers considered this preliminary design optimization problem in the case of superconducting transformers and none of them made a comparison with a validated conventional transformer optimization model. This paper proposes a novel FEM-based two-winding transformer model, which can be used to calculate the main dimension of conventional and superconducting transformer designs. The models are stored in a unified JSON-file format, which can be easily integrated into an evolutionary or genetic algorithm-based optimization. The paper shows the used methods and their accuracy on conventional 10 MVA and superconducting 1.2 MVA transformer designs. Moreover, a simple cost optimization with the 10 MVA transformer was performed for two realistic economic scenarios. The results show that in some cases the cheaper, but less efficient, transformer can be the more economic. [ABSTRACT FROM AUTHOR]