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Abstract In weak-coupling wireless power transmission, increasing operating frequency, and incorporating metamaterials, resonance structures or ferrite cores have been explored as effective solutions to enhance power efficiency. However, these solutions present significant challenges that need to be addressed. The increased operating frequency boosts ferrite core losses when it exceeds the working frequency range of the material. Existing metamaterial-based solutions present challenges in terms of requiring additional space for slab installation, resulting in increased overall size. In addition, limitations are faced in using Snell’s law for explaining the effects of metamaterial-based solutions outside the transmission path, where the magnetic field can not be reflected or refracted. To address these issues, in this work, the concept of a negative equivalent magnetic reluctance structure is proposed and the metamaterial theory is extended with the proposed magnetic reluctance modelling method. Especially, the negative equivalent magnetic reluctance structure is effectively employed in the weak-coupling wireless power transfer system. The proposed negative equivalent magnetic reluctance structure is verified by the stacked negative equivalent magnetic reluctance structure-based transformer experiments and two-coil mutual inductance experiments. Besides, the transmission gain, power experiments and loss analysis experiments verify the effectiveness of the proposed structure in the weak-coupling wireless power transfer system.

Axial-flux magnetic-geared machine (MGM) is a promising solution for electric vehicle applications for combining the virtues of both axial-flux electric machine and magnetic gear. However, generalized MGMs are limited by the torque density issue, accordingly inapplicable to industrial applications. To solve the abovementioned issue, an improved axial-flux magnetic-geared machine with a dual-winding design is proposed. The key merit of the proposed design is to achieve enhanced torque performance and space utilization with the proposed design, which installs a set of auxiliary winding between modulation rings. With the proposed design, overload protection capability, and fault-tolerant capability can be also achieved, for the proposed machine can work with either the excitation of armature windings or auxiliary windings. The pole-pair, slot combination, and parametric design is studied and optimized by the 3d finite-element method and designed C++ optimization software. Electromagnetic analysis and performance comparison indicate that the proposed machine can achieve a torque enhancement of 68.6% compared to the comparison machine.

Abstract In this paper, a novel 3/27/24 (pole pairs of inner rotor permanent magnet [PM]s/modulator/outer rotor PMs) high torque density yokeless magnetic gear with asymmetric Halbach PM array is presented and optimized for electric vehicle powertrain. The key is to improve the torque performance by replacing the magnetic steel with the light nonmagnetic material as the rotor core and employing the embedded magnetic steel bar as well as trapezoidal PM structure to form a low magnetic resistance in the magnetic circuit. The proposed machine has significant performance improvements in two aspects. Firstly, it has high torque density and low iron loss with the yokeless structure. Secondly, it has a high anti‐saturation capability and low torque ripple with the asymmetric Halbach PM array and the embedded magnetic steel bar. The proposed structure is optimized by the co‐simulation of the finite‐element method and C++ optimization software. For a clear evaluation, the proposed structure is compared with generalized solutions in terms of performance and cost. Comparison results indicate that the proposed solution has the highest output torque, torque density, and torque per PM weight among solutions, reaching 214.1 N·m, 58.2 N·m/kg, and 95.6 N·m/kg, which greatly enhances the performance of the magnetic gear.

Recently, the interest in consequent-pole flux-switching permanent magnet (CP-FSPM) machines has been increasing because of the flux-focusing PM arrangements and the removal of the flux-barrier effect. A simple and rigid outer-rotor salient pole rotor structure can be adopted in CP-FSPM machines, making them applicable for in-wheel direct-drive applications. In this study, three CP-FSPM machines with II-shaped (II-PM), V-shaped (V-PM), and straight U-shaped PM (SU-PM) arrays are analyzed and compared. Moreover, a CP-FSPM machine with inclined U-shaped PM (IU-PM) arrays is proposed to improve the flux-focusing effect and stator slot utilization. The working principles of CP-FSPM machines are analyzed by adopting a semi-analytical model. Combining the finite element analysis (FEA) results of air gap flux density and the analytical model of phase back electromotive force (EMF), the contributions of multiple working harmonics to the back EMF are quantitatively analyzed. Additionally, 6/16 and 6/17 CP-FSPM machines with different PM arrangements are globally optimized. Both the no-load and on-load performance of the optimized machines are included in the performance comparison. The results illustrate that the 6/16 and 6/17 machines exhibit their respective merits, and the IU-PM machine shows the best torque production ability in these CP-FSPM machines with the same design criteria.

At present, the majority of electric machine design software employs its own unique machine data structure. However, when users need to transfer their designs between software, they are often faced with significant obstacles or cannot obtain a parametric model suitable for optimization. In order to solve this issue, a universal parametric modeling framework is proposed for electric machine design. The geometric structure is strictly constrained to ensure that the model will not interfere with each part because of the randomness of input parameters. A data structure consisting of points, lines, and surfaces is constructed, and a conversion interface for parametric modeling with different software is established. Consequently, this universal framework can automatically generate parametric models appropriate for different finite element analysis (FEA) software according to the input parameters. The framework is especially convenient for users who need to design or optimize an electric machine, particularly when FEA software is required for verification. Numerical verification is performed using different software based on interior permanent magnet (IPM) synchronous machines to demonstrate the effectiveness of the framework.

Abstract This study proposes a novel power supply system that utilises wind power to produce AC and DC power. A special designed generator based on bidirectional flux modulation effect is the key part of the proposed power supply system. The novel power system has a compact structure since the proposed generator has two electric port. There are three essential points that make the proposed system outstanding. One is the contra‐rotating rotors, which will cluster wind power even under low wind speed. Second one is the dual armature winding structure, which will provide AC and DC power simultaneously. There are two electric port in the proposed generator. One port can produce AC power to the non‐sensitive resistive load. The other can provide AC power with different frequency to the rectifier to obtain DC power. The induced voltage due to flux modulation effect can be used to offer AC power, and the induced voltage due to the outer rotor can be used to offer DC power. The voltage frequency of two sets windings is different. The last one is the air gap flux rotation speed amplification due to flux modulation effect. Time stepping finite element method is used to analyse the dynamic performance of the proposed machine.

A novel dual permanent magnet (PM) machine with Halbach segmentation flux modulation is proposed in this paper, which is evolved from a flux switching PM machine (FSPM). In order to improve the performance of the FSPM, several PM arrangement methods have been adopted and three new different structures have been investigated. To achieve a fair comparison, all the structures are under the same size and rotate at the same speed. The performances of output torque and back EMF are compared. The analysis results show that the dual PM with Halbach segmentation has the highest torque density and power efficiency. The torque is improved by 100.3% from the FSPM while the PM volume does not increase too much. The unique of this best structure is that it not only combines the vernier machine and FSPM machine together, but also reduces the torque ripple. The performance of the motor is verified by the simulation using finite-element analysis (FEA).

A novel dual-airgap permanent magnet Vernier machine (DADPMVM) is proposed and analyzed in this paper. The key of this design is combining the double-concentric-rotor structure, the dual permanent magnet structure along with the Vernier structure to improve the torque density while remaining the motor's volume unchanged. The maximized use of the winding length and the reduction of copper loss are also the main merits of this design. The machine structure and operating principle are discussed, and its transient performance is analyzed by using the finite element method (FEM). Two different configurations of pole pairs and two different structures are designed in the same peripheral dimension configuration and compared with the proposed machine by FEM. The results of the comparison are used to confirm the outstanding performance of the proposed machine. The torque density per machine volume can exceed 100 kNm/ m3 with the proper cooling method.

A novel asymmetric spoke-type interior permanent magnet (AS-IPM) machine is proposed in this paper. It utilizes the magnetic-field-shifting (MFS) effect to improve the torque performance, which achieves a high utilization ratio of both permanent magnet (PM) torque and reluctance torque. In addition, a general pattern of rotor topologies is proposed to represent all possible machine structures. Various rotor structures can be obtained by changing the design parameters of the general pattern. A non-dominated sorting genetic algorithm II (NSGA-II) is adopted to automatically search for optimal rotor configurations. With the aid of the optimization program, an asymmetric spoke-type rotor structure with improved performance is obtained. To showcase the advantages of the proposed machine, the electromagnetic performance is compared between a conventional spoke-type interior permanent magnet (S-IPM) machine and a proposed AS-IPM machine. The finite-element simulation results show that the optimal design of the AS-IPM performs a 7.7% higher output torque ripple due to the MFS effect while the total PM volume remains the same. Meanwhile, the torque ripple of the proposed structure is significantly reduced by 82.1%.

Thrust ripple and density greatly impact the performance of the linear machine and other linear actuators, causing positioning control precision, dynamic performance, and efficiency issues. Generalized pole-pair combinations are difficult to satisfy both the thrust and ripple for double salient reluctance linear machines. In this paper, a DC-Biased vernier reluctance linear machine (DCB-VRLM) is proposed to solve the abovementioned issues. The key to the proposed design is to reduce the ripple and enhance the thrust density with non-uniform teeth by utilizing and optimizing the modulated flux in the air gap. To effectively verify the proposed design, the DCB-VRLMs with different winding pole pairs and secondary poles are compared. The 12-slot/10-pole combination is chosen to adopt a non-uniform air gap structure. Moreover, the energy distribution of AC/DC winding is studied and optimized to further enhance the performance of the proposed DCB-VRLM. The results indicate that the DCB-VRLM with the non-uniform air gap has a lower thrust ripple, better overload capability, and higher thrust density, which confirms its superiority in long-stroke linear rail transit and vertical elevator applications.

Wireless power transmission (WPT) technique has advanced rapidly in the past two decades. For wireless power transmission distances from 40 to 200 mm, the resonance coupling WPT (R-WPT) technique has surpassed its original inductive coupling counterpart in terms of transmission efficiency. Nevertheless, the power transfer efficiency of a R-WPT system is still lower than that of a wired power transfer system. To increase the power transfer efficiency of a R-WPT system, metamaterial (MM) slabs are inserted between the transmitter and receiver. Moreover, it has recently been validated that a hybrid MM (HMM) slab with different resonance frequency unit cells behaves better than a homogeneous MM slab with identical resonance frequency unit cells in a R-WPT application. However, in the existing HMM slab designs for WPT applications, a trial and error approach, is commonly used to decide the physical and circuit parameters of the HMM slab due to the overwhelmingly high computational cost of numerical simulations using three-dimensional (3-D) finite element method. To overcome the deficiencies of the existing designing methodology and to fully automate the design process, a design-of-experiment (DOE) assisted sequential refinement methodology is proposed by introducing an adaptive surrogate model with tabu search method, for design optimizations of HMM slabs in R-WPT applications. Compared with the existing refinement searching procedures, the salient feature of the proposed one is its bi-directional characteristics, which can refine the searches in the promising sub spaces by intensifying sampling points; and use coarse searches or even discarding the exploitations in the worst sub spaces using some adaptive upper and lower limits of the decision parameters. To validate the feasibility and show the advantages of the proposed methodology, detailed numerical and experimental studies on a case study of a four-coil WPT system working at 13.88 MHz are conducted, and the results have shown that the HMM slab optimized by using the proposed methodology does have better performance in WPT applications when compared to its homogenous counterparts.

Almost all of the existing reference vector based finite control set-model predictive control (FCS-MPC) methods for electric machines adopt the deadbeat control principle to directly obtain the reference vector. This paper proposes a computationally efficient control approach for a three phase permanent magnet synchronous motor (PMSM) based on indirect reference vector without using the deadbeat control. Instead of calculating a virtual reference vector in the traditional manner using deadbeat control, the reference vector is innovatively determined through two two-level bang-bang comparators. To improve the performance of the machine, the sampling period is subdivided into two equal time intervals and total 20 synthesized voltage vectors are obtained. Nevertheless, there is no need to evaluate all the 20 vectors by excluding the inappropriate vectors in advance using the reference vector based method, thus reducing the computation time. Moreover, with this proposed method, the complicated calculation of reference vector is avoided. Simulation and experimental results are presented to prove the effectiveness of the proposed method.

Hybrid excited (HE) machines are a potential solution for wind power generation for their high efficiency from permanent magnet (PM) and good flux regulation ability from flexible field current. However, the principle and machine performance of different structures are diverse, which brings challenges in selection of machine topologies and in the dimensional parameter design. Hence, in this article, two machines with different topologies are presented and analyzed to show their merits and demerits. Both machines have relieving-DC-saturation PMs located in the slot openings, while only one of them has consequent rotor PMs to provide an auxiliary flux and to enhance torque production. In this article, the machine structure and working principle are presented, including the relieving-DC-saturation-relieving effect and air-gap field harmonic analysis. For a fair comparison, under the same outer diameter, rated current density, the dimensional parameters of two machines are optimized with genetic algorithm (GA). Further, the machine performance of the optimal models is compared in terms of torque production, back EMF, voltage regulation ability and speed range. The merits and demerits of both machines are summarized in the conclusion.

As asymmetric interior permanent magnet synchronous motor (AIPMSM) has excellent performance but complicated topological structure, a novel high-resolution encoding and edge smoothing method is proposed for topology optimization of the asymmetric rotor of interior permanent magnet synchronous motor (IPMSM) in this study. This method aims to solve complex electromagnetic design problems with time-dependent performance through a multi-objective genetic algorithm (MOGA) integrated with a high-resolution encoding and edge smoothing method. The complex structure is represented by a high-resolution image-like matrix and then vectorized by the edge smoothing method. Therefore, the commonly used discrete binary encoded variables related to the finite element (FE) model are replaced with a vectorized topological structure and other control variables. In this sense, high-resolution matrix and edge smoothing methods are used for the first time to represent the rotor topology of AIPMSMs. Compared with the traditional topology optimization method, the proposed method has the advantage of expressing more complex and vectorized topological structures; meanwhile, the obtained performance is accurate and trustworthy using conventional FE simulation. Numerical results show that a stable convergence is achieved with the avoidance of checkerboards and material overlapping. It is shown that the proposed method can find solutions with better performances, in comparison with the reference model.

The demand for fast magnetic field approximation for the optimal design of electromagnetic devices is urgent nowadays. However, due to the lack of a publicly available dataset and the unclear definition of each parameter in the magnetic field dataset, the expansion of data-driven magnetic field approximation is severely limited. This study presents a physics-informed generative adversarial network (PIGAN), as well as a permanent magnet linear synchronous motor (PMLSM)-based magnetic field dataset, for fast magnetic field approximation. It includes the current density, material distribution, electromagnetic material properties, and other parameters of the electric machine. Physics-informed loss functions are utilized in the training process, making the output governed by Maxwell’s equation. Different slot-pole combinations of the PMLSM are involved in the dataset to extend the generalization of PIGAN. Some indicators for the further evaluation of magnetic approximation performance, including image-based metrics and calculation methods for the performance of electric motors, are presented in this study. Some challenges of magnetic field approximation using PIGAN are also discussed. The effectiveness of the physics-informed method is verified by comparing the magnetic field approximation results and the performance analysis results of the PMLSM with FEM, and the speed of PIGAN is approximately 40 times faster than that of FEM, while the accuracy is similar.

This paper proposes the operation principle and a new flux estimation method for sensorless control strategy for the dual-fed flux modulated electric motor (DFFM). The DFFM is designed based on the flux modulation theory, it includes two stator windings and one rotor which simplify the mechanical structure. The rotor has only modulation iron and no permanent magnets on it, so there is no cogging torque problem in this motor. With adjustment of the outer and inner stator flux rotating frequency and amplitude, different rotation speed and torque of the sandwiched rotor can be gained for the DFFM. Furthermore, an improved flux estimation based sensorless control strategy is performed on the proposed machine to fit the two winding set control situation. The startup and performance of the proposed control strategy is verified by the simulation and experiments.

We propose a novel synthetic slot dual-permanent-magnet (SSDPM) machine with high-torque density for direct drive in-wheel electric vehicles that employ two sets of permanent-magnet (PM) motors. The SSDPM uses both PMs on the rotor and the stator slots, which can achieve flux modulation. The machine's operating principles, based on bidirectional flux modulating effects, need to be further developed. In SSDPM stator slots, PMs are located on the rabbet and on each side of a tooth. The PM is magnetized in various ways and its arrangement is more flexible. A magnet-iron structure is used to provide the flux modulation and PM excitation concurrently. The optimal design adopts a combined method that uses a finite element method and a genetic algorithm. The performance of this hybrid method is analyzed by simulation. A prototype machine is manufactured and the experimental results verify the validity of the model structure and simulation results.

Nanofluid is an innovative approach to improve the thermal conductivity of fluid by adding nanoparticles. Transformer oil-based nanofluids have been prepared and measured, which verifies the concept and demonstrates the potential in oil-immersed power transformer applications. In this paper, the effect that nanofluids (oil/SiC) have on the natural convective heat transfer in disc-type transformer windings is investigated numerically. The multi-phase mixture model is employed for the first time to analyze such a nanofluid flow field, and the single-phase model is also used for comparison and mutual authentication. After using the nanofluid, significant temperature drops inside the windings are observed, and in some cases, the heat transfer performance is further improved by the adjusted mass flow rate distribution. The impact of nanofluids is enhanced with the rising volume fraction of nanoparticles. Before performing the study, the numerical model is validated using the existing results of the referenced windings cooled by transformer oil.

In-wheel direct drive (IWDD) of electric vehicles (EVs), which simplifies the transmission system and facilitates flexible control of vehicle dynamics, has evolved considerably in the EV sector. This paper proposes a novel double-stator double-rotor motor (DSDRM) with a bidirectional flux modulation effect for in-wheel direct drive of EVs. With the proposed special design, a synthetic-slot structure with synthetic materials containing copper and permanent magnets (PMs) in the slots of the motor is ingeniously employed, and the outer and inner rotors are mechanically connected together as a single rotor, making its mechanical structure less complicated than those of two-rotor machines. The main work of this paper involves the design, analysis, construction, and testing of the proposed machine. The DSDRM with a synthetic-slot structure was demonstrated to be feasible by finite element analysis (FEA), prototype fabrication, and experimental results. In addition, vehicle layout with DSDRM is presented and verified by the vehicle road test experiment. Thus, the DSDRM with the synthetic-slot structure can be used as a hub motor for in-wheel direct drive of EVs.

As an innovative approach to improve the cooling efficiency of fluid, the use of nanofluids has attracted increasing attention in engineering applications. In this paper, the impact on the natural convective heat transfer in disc-type transformer windings due to transformer oil-based nanofluids is studied numerically. A low-voltage winding using nanofluid (SiC/oil) as the coolant is modelled two-dimensionally and simulated by computational fluid dynamics and the multi-phase mixture model. The numerical method is validated with the existing results of transformers using conventional oil cooling, and grid-independence study is carried out for the nanofluid flow. Compared with transformer oil cooling, the temperature of nanofluid cooled winding is significantly reduced, while the temperature trend along the flow direction remains essentially the same. Moreover, the effects of nanofluid on the mass flow rate and the coolant temperature have been taken into consideration in the heat transfer analysis.

In this paper, a permanent magnet (PM) linear memory machine is proposed for ocean wave power generation. A notable feature of this machine is its online tunable mnemonic flux. This enables it to operate efficiently in a wide speed range and makes it suitable for the variable-speed wave-power generation. Moreover, this machine has both the PMs and the windings arranged in its stator so that it does not need slip rings or brushes. The proposed machine is also robust and cost-effective because it has a simple translator of slotted steel. In this paper, the configuration and working principle of the linear memory machine are firstly introduced. The results of a parametric analysis are presented to investigate the effects of the proposed machine’s geometric parameters. The performance of the proposed machine is then analyzed using time-stepping finite element method (TS-FEM).

With the continuous development of machines, various structures emerge endlessly. In this paper, a novel 6-stator-coils/17-rotor-teeth (6/17) E-shaped stator tooth flux switching permanent magnet (FSPM) machine is introduced, which has magnets added in the dummy slots of the stator teeth. This proposed machine is parametrically designed and then compared with the conventional 6/17 E-shaped stator tooth FSPM machine through finite element method (FEM) analysis. Then, combined with the results of FEM, the performance of two machines is evaluated, such as electromagnetic torque, efficiency, back electromotive force (back-EMF). The final results show that this novel 6/17 FSPM machine has greater output torque and smaller torque ripple.

The memetic algorithms which employ population information spreading mechanism have shown great potentials in solving complex three-dimensional black-box problems. In this paper, a newly developed memetic meta-heuristic optimization method, known as shuffled frog leaping algorithm (SFLA), is modified and applied to topology optimization of electromagnetic problems. Compared to the conventional SFLA, the proposed algorithm has an extra local search step, which allows it to escape from the local optimum, and hence avoid the problem of premature convergence to continue its search for more accurate results. To validate the performance of the proposed method, it was applied to solving the topology optimization of an interior permanent magnet motor. Two other EAs, namely the conventional SFLA and local-search genetic algorithm, were applied to study the same problem and their performances were compared with that of the proposed algorithm. The results indicate that the proposed algorithm has the best trade-off between the results of objective values and optimization time, and hence is more efficient in topology optimization of electromagnetic devices.

Dispersing nanoparticles with high thermal conductivity into transformer oil is an innovative approach to improve the thermal performance of traditional oil-immersed transformers. This mixture, also known as nanofluid, has shown the potential in practical application through experimental measurements. This paper presents the comparisons of nanofluid filled transformer and traditional oil-immersed transformer in terms of their computational fluid dynamics (CFD) solutions from the perspective of optimal design. Thermal performance of transformers with the same parameters except coolants is compared. A further comparison on heat transfer then is made after minimizing the oil volume and maximum temperature-rise of these two transformers. Adaptive multi-objective optimization method is employed to tackle this optimization problem.

This paper proposes a dynamic multi-level optimal design method for power transformer design optimization (TDO) problems. A response surface generated by second-order polynomial regression analysis is updated dynamically by adding more design points, which are selected by Shifted Hammersley Method (SHM) and calculated by finite-element method (FEM). The updating stops when the accuracy requirement is satisfied, and optimized solutions of the preliminary design are derived simultaneously. The optimal design level is modulated through changing the level of error tolerance. Based on the response surface of the preliminary design, a refined optimal design is added using multi-objective genetic algorithm (MOGA). The effectiveness of the proposed optimal design method is validated through a classic three-phase power TDO problem.

This paper presents a novel hybrid-flux magnetic gear, which integrates a transverse-flux magnetic gear and an axial-flux magnetic gear into a single unit. Compared to its conventional counterparts, the proposed magnetic gear transmits a relatively high torque density. When compared to the transverse-flux magnetic gear, this new structure employs an extra iron segment between the low-speed rotor and high-speed rotor to modulate the magnetic field and contribute to the transmission of additional torque. A three-dimensional (3-D) finite element method (FEM) is used for the analysis of the magnetic field. In the paper a variables-decoupling method based on the sensitivity analysis of the design parameters is also presented to accelerate the optimization process of the proposed machine.

A new squirrel-cage rotor structure induction motor (IM) that has a auxiliary permanent magnet (PM) rotor and improved cage-rotor structure is presented to enhance the inherent power factor of the IM, and a prototype motor is fabricated by modifying the rotor of a conventional three-phase four-pole squirrel-cage induction motor. The flux linkage, flux distribution, power factor, core loss and efficiency of the novel and conventional rotor structure induction motor are comparative analyzed. The 2D transient finite element analysis method is used for computation the characteristics of the two induction motors.

A general pattern, which can include different types of permanent magnet (PM) arrangement in PM synchronous motors (PMSMs) is presented. By varying the geometric parameters of the general pattern, the template can automatically produce different types of PM arrangement in the rotor. By choosing the best arrangement of PMs using optimization method, one can obtain a better performance and lower manufacturing cost. Six of the most widely used conventional types of rotor structures can be obtained through the parameter variation of the general pattern. These types include five embedded PM types and a traditional surface-mounted PM type. The proposed approach combines optimization method embedded with finite element method (FEM) for solving the multi-objective optimization for the PM structures. To save computing load, this paper employs a strategy of sub-group optimization, which is on account of the impact levels of the design parameters on the objective functions, and a parallel computation, which is a valid method to shorten the computing time. As an application example, a PMSM is optimally designed. Its simulation results and prototype experiments are provided to showcase the effectiveness of the proposed method.

This paper presents the control strategies for a novel dual-stator flux-modulated (DSFM) motor for application in electric vehicles (EVs). The DSFM motor can be applied to EVs because of its simple winding structure, high reliability, and its use of two stators and rotating modulation steels in the air gap. Moreover, it outperforms conventional brushless doubly-fed machines in terms of control performance. Two stator-current-oriented vector controls with different excitation in the primary winding, direct and alternating current excitation, are designed, simulated, and evaluated on a custom-made DSFM prototype allowing the decoupled control of torque. The stable speed response and available current characteristics strongly validate the feasibility of the two control methods. Furthermore, the proposed control methods can be employed in other applications of flux-modulated motors.