Conference Agenda

The adaptive modulation of temperature distribution is an emerging challenge for advanced induction heating applications. In a portable heater with solenoidal coils, induction coils exhibit a high packing factor to achieve high power density. Therefore, the modulation of the heat source distribution becomes difficult to achieve using traditional coil design methods owing to the lack of design variables. Therefore, this study proposes wireless power transfer-based induction heating for flexible controls of the heat source distribution. The proposed model can help adjust the heat source distribution without changing the coil structure. The amplitude and phase of the transmitter and receiver coil currents were investigated to demonstrate their combined effect on the heat source distribution. The resonant frequencies of the primary coil and the secondary coil are set to the design variable to determine a feasible combination of the amplitude and phase of the Tx and Rx coil currents, and it is possible to independently modulate the amplitude and phase of the transmitter and receiver coil currents. The results demonstrate that the proposed model can achieve the desired temperature distribution.

This paper proposes a nonlinear analytical model embedded optimal design procedure for permanent-magnet synchronous motors with external rotor. Combined with the winding inductance calculation, a refined magnetic circuit is proposed for the analytical prediction of the electromagnetic performance. The stator nonlinearity, which is the key of average torque prediction, is taken into account by the introduction of saturation current. Ant colony algorithm is employed for the multi-objective optimization for the strong potential in global exploring. Then, design parameters are optimally selected from the Pareto front. The effectiveness of the proposed optimization design method is verified by finite-element analysis.

In this work, different types of machines are designed and optimized for a fully electric regional aircraft. The machines are designed using a multiphysics model for different rotational speed values in order to study the advantage of increasing speed. A pre-design and pre-optimization process based on fast modeling allows selecting machines that meet aircraft specifications. Selected candidates are then optimized using a fine design and are compared based on their specific power and efficiency.

This paper presents multi-fidelity topology optimization of a portable low-field magnetic resonance imaging (MRI) device to realize high magnetic uniformity as well as to reduce its weight. The proposed method performs low-fidelity optimization of an iron yoke and high-fidelity optimization of shimming magnets and iron blocks which are much smaller than the iron york. It is shown that the proposed method reduces the weight by 32% compared to the MRI and achieves a magnetic uniformity of 700ppm

This paper proposes a novel methodology for multi-material topology optimization (multi-TO) based on projective transformations (PT) and Boolean operations (BO). Specifically, several basic components (BC) are selected to constitute a new topology. The PT and BO are employed to represent the evolvement of each BC and the way of combination between each pair of the BC. Moreover, the mechanism that can deal with multiple materials is developed. The numerical result has validated the proposed methodology.

Higher-order mode (HOM) couplers are devices used to dampen the parasitic HOMs excited in accelerating cavities due to the interaction of the electromagnetic fields of the charged particles traversing the cavity with the cavity walls. These HOMs either

deflect the charged particle off the desired trajectory or reduce acceleration efficiency, which adversely affects beam dynamics and stability and could even result in beam loss. Coaxial HOM couplers are intricate devices consisting of several sections. Numerous variables are required to parameterize HOM-coupler computer models. In designing and optimizing such devices, it is essential to know to which variables the quantities of interest (QOIs) are most sensitive to reduce the number of input variables considered. The objective of this work is two-fold. The first is to study the global sensitivity of some QOIs of a hook-type HOM coupler versus several geometric variables to identify the number of key geometric variables considered in optimizing or tuning such devices. Secondly, a local sensitivity analysis is carried out to provide the sensitivity of the hook-type HOM coupler designed for the W working point of the Future Circular electron-positron Collider (FCC-ee).

This paper investigates the optimal design of a permanent magnet-assisted synchronous reluctance motor (PMa-SynRM) for electric vehicles using the novel high-level surrogate model based on variable sensitivities. The proposed method improves the optimal model search performance by utilizing the sensitivities of each structural design variable for the optimal design of PMa-SynRM with multiple design variables. As a result, a successful and optimal PMa-SynRM design with a 1.77% increase in average output torque and a 27.89% reduction in torque ripple was derived. These results confirmed the validity of the method proposed in this paper and can be expected to be applied to various designs.

With the development of additive manufacturing technology, studies of microstructure for designing physical properties are being actively conducted and widely used in magnetic devices. This type of equipment must consider multiphysics phenomena such as electromagnetics and elasticity. To improve the performance of machines, research on multifunctional materials is essential. Therefore, an inverse homogenization method that simultaneously adjusts the magnetic and mechanical properties of the structure was proposed. The effective properties were derived using the periodic cell theory-based homogenization method, and topology optimization was carried out. To control flux densities and maximize structural stiffness at the same time, the prescribed nonlinear permeability was set as a constraint, and the maximization of bulk or shear modulus was selected as the objective function. Consequently, optimum microstructures increased by 9.91% for bulk and 94.38% for shear modulus was calculated while satisfying the same target permeabilities. The optimum design with shear modulus demonstrated significantly improved multifunctional characteristics. This design method can be extended to multiscale optimization and possibly applied to electro-mechanical machinery.

A fast and efficient method to design induction machine from different electromagnetic and thermal constraints has always been a challenging problem. Quick estimation of machine’s dimensions is important in the sales tool to provide quick quotations to customers based on specific requirements. The key part of this process is to select different design parameters like length, diameter, tooth tip height and winding turns to achieve certain torque, current and temperature of the machine. Electrical machine designers, with their experience know how to alter different machine design parameters to achieve a customer specific operation requirements. In this work, a reinforcement learning algorithm is proposed to mimic a machine designer workflow and train a neural network to quickly design a customised induction motor. The neural network model is trained by playing “different games” of electrical machine design with a reward or penalty function when a good or bad design choice is made. The results demonstrate that the suggested method automates electrical machine design without applying any human engineering knowledge.

For the optimal design of electrical machines, finite element analysis-based research requires repeated time consumption. To address this problem, in this paper, the species-conservation harmony search algorithm (SHA) is proposed as a multimodal optimization algorithm. The proposed SHA can effectively preserve the diversity of solutions and quickly find solutions by utilizing the species-conservation technique. To verify the reliability and performance of the proposed SHA, an evaluation reference value is obtained by applying it to a test function. Furthermore, the optimal design of the consequent-pole wound-rotor synchronous motor is conducted by using the proposed algorithm. The average torque according to the magnet angle is selected as the design variable. The final design is derived by considering the torque ripple characteristics and magnet usage among the searched global and regional optimum points.

In this article, a multi-physical topology optimization (TO) is applied to the design of a synchronous reluctance motor (SynRM) using the Generalized Optimality Criteria (GOC) method. A multi-step magneto-mechanical optimization is applied to ensure structural robustness of the rotor. Magnetic and mechanical objective functions are formulated considering respectively the magnetic energies, obtained with a d-axis and q-axis stator currents, and the mechanical compliance. The gradient of the two objective functions considered in the algorithm are calculated with the adjoint-variable method.

In shape optimization of electromagnetic devices using the finite element simulation, to avoid the cumbersome remeshing process during the geometric parameter sweep, an efficient mesh deformation method preserving the mesh topology is essential to shorten the computation time and ensure the accuracy. This paper proposes a gradient-based mesh deformation method to avoid the mesh overlapping and limit the deformed bad quality elements for large shape variation. Based on the solution of Laplace equation, a gradient-line algorithm is introduced to move the mesh nodes accordingly with the geometry change. To handle the movement of mesh nodes on certain geometry borders, the Neumann boundary constraint is employed. 2-D numerical examples are reported to demonstrate the effectiveness of the proposed method.

Rare earth permanent magnets can achieve high efficiency of motors due to their high magnetic performance. However, due to scarcity, the price is formed high and it is difficult to obtain a stable supply. Due to this seriousness, measures to reduce the dependence on rare earths are needed. A primitive solution is to use a motor that does not use rare earth elements. However, this is not suitable as a solution because the performance is very poor compared to rare earth motors. The second method is to use non-rare earth ferrite permanent magnets. If ferrite permanent magnets are simply applied to conventional motors, their performance is lower than that of rare earth motors. However, when a ferrite permanent magnet is applied to a magnetic flux concentration type structure that has been recently studied, it has performance similar to that of a motor using rare earth elements. Furthermore, studies have been conducted that can additionally utilize reluctance torque by modifying the existing magnetic flux concentration type structure. In this paper, design variables are added to further improve the performance of the above structure. In addition, the performance analysis of the redesigned motor and the conventional motor was performed.

Recently, research and development of ultra-high-speed permanent magnet motors for high power, high efficiency, and miniaturization are being conducted. In order to achieve high performance in the high-speed rotation range, cogging torque, torque ripple, and THD must be small, and in order to achieve high efficiency, the loss generated by the motor must be small. Slot-type high-speed permanent magnet motors need to improve eddy current loss, torque ripple, vibration and noise due to harmonics. In contrast, a slotless motor with no cogging torque, which is a cause of vibration and noise, has a structure without teeth and slots, and has low THD and torque ripple, enabling stable operation. In addition, due to structural characteristics, slotless type motors are more advantageous for miniaturization. In this paper, we propose an optimal design process for a slotless type motor, design a 7kW slotless high-speed permanent magnet motor based on it, and analyze its performance.

This paper proposes topology optimization of a switched reluctance machines to minimize the torque ripple under the constraint of an average torque. The novelty is targeting torque's harmonic content. The topology optimization is solved using a gradient-based algorithm, and the derivation of the gradient for the proposed formulation is developed by the adjoint variable method.

Multi-material topology optimization has an advantage on design optimization of asymmetric interior permanent magnet synchronous motor (IPMSM) with a high degree of freedom, determining material distribution of permanent magnet (PM) core and air. However, during the optimal design process, manufacturability of the permanent magnet deteriorates, degrading design realization and. In order to prevent these problems in previous studies the segmented PM magnetization target direction even at the risk of performance degradation. In this study, we introduce a multi-Heaviside projection method for PM manufacturability on multi-material topology optimization that can perform optimal design for both magnetization direction and target angles. This method is a modification of the Heaviside projection method in the density-based topology optimization, which gradually penalizes design variables in the optimization process and projects magnetizing direction variables to target angles. The sensitivity for the target angle of the modified Heaviside projection function is also derived, and the optimum target angle improving the performance of IPMSM is obtained together by performing the optimal design by additionally setting it as a design variable. As a result, an optimal design algorithm that guarantees productivity while having the optimal material distribution and magnetization direction of the asymmetric IPMSM rotor is established and verified through a numerical example of an 8-pole 48-slot traction motor.

Shelf life of a wine depends on its stability with respect to several factors, including microbiological, chemical, and physical evolution. These influence the quality of the wine, perceived by the consumer as color and sensory appeal. The traditional processing of liquid foods, like thermal processing, or the addition of sulfur dioxide, improve the capability of withstanding time, but degrade the wine’s flavor and taste. Sterilization processes based on Pulsed Electric Field (PEF) have been introduced recently for fruit juices. PEF processing has proved to be an alternative technique also for wine treatment, able to selectively reduce the presence of unwanted yeasts. To achieve an effective treatment, the electric field must be as uniform as possible within chambers large enough to host amounts of wine significant for food industry. The aim of this study is to optimize the shape of the chamber plates, their connections to the (pulsed) power supply, and voltage waveforms, to obtain a satisfactory field level and time behavior. In this digest, just some preliminary numerical experiments are reported to show the relevance of the issue when significant volumes of excited region are considered, and some indications about the optimization approach are provided.

This paper investigates the multi-material topology optimization of the 3-phase stator of an electrical machine. The density-based optimization framework uses a gradient descent on the candidate materials’ physical properties (magnetic polarization, current density). The results indicate that a smoothing procedure is necessary to avoid non-manufacturable designs and promotes a broader exploration of solutions. In addition, a current angle adjustment accelerates the convergence. Based on these results, an efficient optimization procedure that couples both techniques is proposed.

Although the output of an induction motor (IM) is lower than that of an interior permanent magnet synchronous motor, IMs are widely used in industrial field due to their robustness, low cost, self-starting characteristics, etc. As a good measure for designing a high-performance IM, there is a fast design method that combines magnetic field analysis using finite-element method with sensitivity-based topology optimization using time-domain adjoint variable method (TDAVM). However, TDAVM consumes a lot of memory as it requires state variables such as the magnetic vector potential at all time steps in the time domain. To reduce the memory consumption caused by the storage of state variables, the approximation method of state variables in the time domain using a hybrid method comprising linear interpolation and Fourier series is proposed in this paper.

To promote decarbonization, the demand for motors is increasing in the field of transport. Although high efficiency interior permanent magnet synchronous motors (IPMSMs) have been widely used, a stable supply of rare-earth permanent magnets is not always guaranteed due to the geopolitical risks involved. Therefore, switched reluctance motors (SRMs) which comprise only an iron core, shaft, and windings, and are low-cost and robust, have attracted attention recently. In this study, a magnetic field analysis method, strongly coupled with an asymmetric half-bridge converter to improve the torque characteristics of SRMs, is proposed.