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The variable frequency transformer VFT is investigated in this research for a new type of grid interconnection solution Taking advantage of the moment of inertia of the rotor the ability of the power system on coping with the sudden fluctuation can be enhanced Aiming at a feasible design in this application condition the design requirement is firstly specified based on the application configuration and operation principle and kinetic energy analysis of the VFT The distribution relationship between electromagnetic power and mechanical power as well as the effects of torque change and grid side frequency change on power transmission are analyzed to provide reference for the stable transmission and reliable control of VFT power Then to meet the design specification the design process is summarized The design result is verified in a 15 kW design example and test platform

To extend the automatic design process of the interior permanent magnet synchronous motors IPMSM a density based topology optimization approach of the rotor is developed in this research Considering the torque performance as the objective the topology optimization is conducted under the constraint of the mechanical performance and electromagnetic performance including the structural strength and the torque ripple respectively A validation example of an IPMSM is used to prove the effectiveness of the developed optimization

The properties of electromagnetic materials play a key role in designing electromagnetic devices such as electrical machines and transformers Although the magnetic fields in these devices are generally two dimensional 2D or even three dimensional 3D and rotational the material properties obtained from one dimensional 1D alternating magnetization are commonly used due to the lack of available data This has hindered the development of high performance electromagnetic devices such as high speed high power density electric motors This paper aims to present an overview about the characterization of 2D 3D vectorial magnetic properties of various advanced electromagnetic materials such as soft magnetic composite nanocrystalline and amorphous magnetic material magneto rheological fluid and elastomer and high temperature superconductor

Switched reluctance motors SRM have the features of high adaptability simple structure low maintenance cost and high torque power capabilities which gained a worldwide reputation The SRMs have made recent advancements in electric vehicle applications indicating their potential to replace conventional and permanent magnet PM motors The hybrid excitation of SRM HESRM method is one of the predominant methods that incorporate rare earth metals in the conventional SRM to enhance the torque performance by increasing the air gap flux density However the HESRM approach using PMs suppresses the unique features of SRMs through secondary excitation with PMs In this paper a new topology is introduced to improve the average torque of HESRM without employing PMs The stator iron is segmented and replaced with high permeable material to the auxiliary coils to ensure the maximum torque capability through segmented HESRM SHESRM Furthermore the machine s static and dynamic characteristics are investigated using the 2D finite element approach 2D FEM The results of the proposed motor are compared and validated with experimental analysis with the same machine rating The findings show that the machine has maximum average torque in a wide speed range The advantages of high fault tolerance redundancy and reliability prove that the proposed motor has a high potential for traction purposes

This paper proposes a data driven iron loss estimation method to reduce the calculation time of iron loss in bearingless permanent magnet synchronous motors BPMSMs The iron loss calculation dataset is obtained by design of experiments and the iron loss prediction model is established under different input parameters and working conditions Firstly the stator core flux density changing rules at selected points are analyzed and the flux density components of different parts of iron loss are studied Secondly the effects of temperature and frequency on iron loss are studied Finally a data driven iron loss estimation method is established based on the nonlinear autoregressive exogenous NARX model using input current frequency and temperature data In the proposed method the iron loss of BPMSM under all working conditions is considered which significantly shortens the calculation time compared to the finite element analysis This method can be used to quickly obtain the iron loss variation range of each speed and different working conditions and provide a basis for calculating motor efficiency and design optimization

In this paper we present a hybrid deeplearning forecasting method based on heating and cooling degree days data to predict the electricity demand in Australia The proposed model integrates convolutional neural network CNN and long shortterm memory LSTM models to improve electricity prediction accuracy The proposed model performance is comprehensively compared with a few conventional forecast methods including deep neural networks DNN model The results show that the mean absolute error and mean absolute percentage error of the prediction have been reduced by using the proposed hybrid model

Accurately calculating iron loss in the extensively used interior permanent magnet synchronous machines IPMSMs is challenging due to the effects of temperature variations which can also be significant in automotive applications for optimizing efficiency While the finite element method is a valuable tool for simulating and analyzing complex systems including electric vehicle EV traction motors it is essential to be aware of its limitations on computational cost and potential challenges when calculating iron loss in analyzing multi physics effects Therefore this paper presents a comparative iron loss analysis between the improved analytical iron loss calculation model finite element results and experimental measurements of an IPMSM used in EVs with a specific focus on considering the effects of temperature variation By investigating the impact of temperature changes on iron loss by these obtained data this study aims to provide valuable insights into validating the improved model s accuracy assessing its computational efficiency and identifying potential areas for improvement

Battery pack Remaining Useful Life RUL prediction stands at the crossroads of technology and sustain ability in electrified transportation and energy storage This review journeys through the landscape of RUL prediction from the traditional empirical models to the cutting edge machine learning techniques It is a technical analysis and a narrative of evolution challenges and possibilities The paper delves into the complexities of data quality algorithm intricacy and real world applicability casting a critical eye on the road ahead It calls for collaboration innovation and a shared vision for a future where battery systems are efficient and resonate with our broader sustainability goals

This article proposes a torque enhancement strategy for asymmetrical six phase PMSMs First specific fifth and seventh harmonic currents are injected into the harmonic subspace and reference current benchmarks are set to achieve the desired torque enhancement Then the influence of harmonic plane back electromotive force on the response current is studied and the deadbeat harmonic predictive current control DHPCC equation considering lumped disturbance is derived Furthermore an extended state observer ESO is considered to improve control performance of the proposed strategy Finally the experimental results demonstrate the superiority and effectiveness of the proposed scheme

It is difficult to accurately calculate the iron loss in electric propulsion systems for electric vehicles (EVs) with traditional models due to the complicated effects of temperature variations and supply current harmonics on magnetic material properties. In order to improve the performance of interior permanent magnet synchronous motor (IPMSM) drive system in EVs, this paper proposes an improved iron loss analytical model for IPMSM, aiming to consider the multi-effects of iron loss versus temperature and harmonics, as well as to reduce the huge computational costs compared with finite-element method. To guarantee the modeling accuracy, the influences of temperature variations and various supplies on silicon steels are investigated carefully by the developed magnetic measurement platform. Moreover, considering that the frequency, power and temperature of drive systems would vary continuously in the operating mode, the proposed models are also applied to an IPMSM prototype for analyzing the iron loss during a dynamic drive cycle, rather than at a stable working point. Experimental comparative results show the satisfactory accuracy and less computational burden of the proposed model, even in a dynamic drive cycle of EV.

The permanent magnet claw pole machine (PMCPM) with hybrid cores investigated in this paper is a new claw pole machine (CPM) with the modular design where its stator is composed of stator yoke made by silicon sheet and stator claw pole teeth made by soft magnetic composites (SMC). As the PMCPM is with very complex 3D structure and there is a great number of design parameter needs to be determined, optimizing the PMCPM is very time consuming and using the traditional multilevel optimization strategy (MOS) is an effective way. In this paper, the parametric analysis is proposed as a pre-design to the MOS, and a parameter-oriented grouping (POG) method based on parameter analysis is proposed to improve the optimization speed of MOS. Specifically, the objectives and design parameters are streamlined and grouped by using inter-objective correlation analysis (CA), parameter-to-objective sensitivity analysis (SA), and inter-parameter correlation analysis (RA) method, then the MOS is performed based on the parameter analysis results. The traditional MOS method are employed for the benchmark comparison, and the effectiveness of the proposed MOS based on POG is verified by the experiment.

The worsening in oil resource crisis and climate change has contributed to the widespread investigations and applications of electric vehicles (EVs). Meanwhile, the performance of electrical drive systems, as the most important power unit, corresponds directly to the operational stability, reliability and economy of EVs. This paper proposes a system-level design optimization approach for the EV drive system with an interior permanent magnet synchronous motor (IPMSM), targeting improved system efficiency, reduced torque ripple and minimal costs. Specifically, an improved system-level loss model, considering both the motor and control system losses, is presented for objective efficiency calculation. Moreover, to handle the high dimensional and nonlinear problem, the multi-level optimization strategy is employed, in which four subspaces containing parameters in both motor and control levels are defined based on the sensitivity to the objectives. The approximate models and optimization algorithms are utilized to reduce the computation cost of finite element analysis in each level. Finally, the proposed approaches are investigated with a practical IPMSM drive system used in EVs. Results illustrate the effectiveness and show that the proposed multi-level design optimization method with the improved system-level loss model can obtain parametric optimums, while maintaining better steady-state and dynamic system performances.

To enhance the optimization and control efficiencies of the interior permanent magnet synchronous motor (IPMSM) drive system for electric vehicles (EVs), an improved multi-objective design optimization strategy at the system level is proposed in this paper. To handle the high dimensional and nonlinear problems for searching Pareto optimal solutions, the multi-level optimization algorithm with approximate models is utilized, by which the computational cost can be greatly reduced. In terms of the typical specifications and requirements of EVs, the maximum torque, minimum torque ripple, and minimum speed overshoot are set as the optimization objectives. For further improving the optimization accuracy and search speed, the objective of minimum loss is achieved through the loss minimization control algorithm instead of being solved in each optimization level, by which the system efficiency is also promoted. Experimental and numerical results show that the proposed approaches can effectively solve the design optimization issues of electric drive systems, and enhance the static and dynamic system performance.

Switched reluctance motors SRMs have become more prevalent in electric traction motors because they operate at high speeds have optimum control and can improve electrically driven performance with multiple phases overlapping This can be attributed to their maximum torque per ampere and power density The design and development of specialized electrical machines like SRMs have proliferated in recent years as an alternative to DC series and permanent magnet based PM motors This paper presents the design consideration and the performance evaluation of a hybrid excited non permanent magnet assisted switched reluctance motor for electric vehicles EV applications The hybrid excitation of switched reluctance motors HESRM is attracting considerable demand in the EV market due to its high torque performance However this method is currently incorporated with PM assisted excitation to enhance the performance of SRMs This newly designed hybrid excitation method enhances torque performance without using rare earth elements by injecting direct current DC through the designated auxiliary poles The novel machine s static characteristics and dynamic performance are simulated and compared with the conventional SRM drives of the same ratings Consequently two motor prototypes are redesigned and the concept is validated through experimental analysis In all speed ranges the proposed topologies provide significantly greater electromagnetic torque than the conventional ones Because of its fault tolerance multiple control topologies and redundancy were attained thus making this machine well suited for EV applications

The commercialization and development of electric and hybrid electric vehicles (HEVs) are one of the main steps in transportation electrification. The design of the optimum electric machines as the fundamental part of the propulsion system of electric vehicles (EVs) and HEVs is of great importance. The optimization of the electric machine in large search space is not practical. Therefore, it is crucial to provide an initial design to limit the optimization variables and reduce the search space. This paper aims to provide a step-by-step guideline for the design of an axial flux permanent magnet synchronous machine (AFPMSM) that operates as a direct drive machine in an HEV. The performance of the designed machine is validated using 3-D finite element analysis results. The designed AFPMSM performance parameters are reported over a wide range of operating points within the torque speed envelope.

Electromagnetic vibration is excited by the radial electromagnetic force generated by the air gap magnetic field acting on the stator core In this paper an analysis and reduction of electromagnetic force in high speed permanent magnet electrical machines with different stator cores are investigated A fast and accurate calculation method of air gap flux density and radial force density distribution are derived The radial force density including amplitude frequency and order is obtained by a two dimension fast Fourier transform Then the effect of the different PM segmentation on radial force is summarized

This paper proposes a novel fully predictive control FPC for permanent magnet synchronous machine PMSM which adopts the techniques of online parameter identification and position sensorless The FPC comprises a speed outer loop and a current inner loop Online parameter identification with recursive least squares RLS OPI is used to get PMSM s resistance magnetic linkage and inductance Position sensorless with a derivative free disturbance observer DFDO is used to obtain the speed and torque The simulation and experimental results show that the proposed control algorithm has a faster response and better dynamic performance in different temperatures

This paper proposes a Particle Swarm Optimization (PSO) Recursive Neural Network (RNN) method independent of the empirical iron loss formula to analyze the iron loss in a permanent magnet synchronous motor (PMSM). This model establishes an iron loss calculation model considering high-order harmonic, rotating magnetization, and temperature factors. Considering the influence of multi-factors, the model studies the law of loss change under different magnetic flux densities, frequencies, and temperature conditions. To avoid the deviation problem caused by traditional polynomial fitting, the multi-layer RNN and PSO are used to train and optimize the neural network. Using the machine learning method, the iron loss model versus input parameters is established. The iron loss in complex cases beyond the measurement range can be estimated accurately. The proposed method helps achieve a PMSM iron loss calculation model with broad applicability and high accuracy.

The interior permanent magnet synchronous machine IPM with a double layer permanent magnet PM rotor structure is a good candidate machine for electric vehicle drive systems due to its high torque ability and efficiency however it also has the disadvantages of high cogging torque and high vibration noise Improving the air gap flux density distribution is an effective way to reduce the cogging torque and vibration of the electrical machine which can be achieved by designing the rotor surface with auxiliary slots The torque performance and vibration of the IPM can be affected by the shape position and number of auxiliary slots on the rotor surface In this paper the rotor auxiliary slot structure of double V shaped permanent magnet IPM D V IPM is optimized with cogging torque and air gap electromagnetic density as the optimization objectives then the influence of the rotor auxiliary slot on the torque performance and vibration of D V IPM are summarized A multi objective genetic algorithm MOGA was used to optimize the design of the D V IPM with four curved auxiliary slots F CAS and the motor performance was verified by experiments

As no permanent magnet (PM) material is required and only silicon sheets are needed on the rotor core, the synchronous reluctance machine (SynRM) has received tremendous research attention in the past and it can be used for many driving applications. However, compared with the electrical machine with PM excitation, its torque density, efficiency, and power factor are both low. In this paper, a novel SynRM with hybrid cores (Hybrid-SynRM) is proposed. Specifically, its rotor core is made by the combination of non-grain-oriented (NGO) silicon sheet cores and grain-oriented (GO) silicon sheet cores. The magnetic circuit characteristic of the proposed Hybrid-SynRM is improved by taking the super high magnetization characteristic of the GO silicon sheet along its rolling direction. To verify the performance of the proposed SynRM, the traditional SynRM with NGO silicon sheet cores (NGO-SynRM) is determined as the benchmark machine. For obtaining fair comparison results, both these two machines are optimized under the same conditions. Through the comparison, it can be seen that the torque ability, efficiency, and power factor can be improved greatly by employing the GO silicon sheet block in the SynRM. Therefore, the Hybrid-SynRM can output better performance than the NGO-SynRM especially when the applied electrical loading is high.

The interior permanent magnet synchronous motor (IPMSM) is widely used for electric vehicle driving applications since it has high torque and efficiency. However, torque ripple is very high which is a main drawback of the IPMSM. Its torque ripple can be reduced by designing the auxiliary slots on the rotor and stator surfaces and designing its permanent magnet and flux barrier with an asymmetric structure. Meanwhile, the design parameters will be increased greatly if the above design methods are employed for the IPMSM, which will make the machine difficult to design and optimize. In this paper, a four-stage multi-level optimization design process (FSMLODP) is proposed to optimize IPMSM with the double-layer asymmetric and rotor auxiliary slot structure for achieving low torque ripple performance. The effectiveness of the proposed FLMLODP is verified by three different IPMSMs, it can be seen that the torque ripple of IPMSM can be reduced greatly by taking asymmetric and rotor auxiliary slot design for the IPMSM. The torque performance of optimal IPMSMs using conventional asymmetric main parameter design optimization (CAMPDO) methods and FSMLODP was compared and verified FSMLODP is effective and efficient.

The interior permanent magnet synchronous motor (IPM) for electric vehicle drive has the disadvantages of high torque ripple and high vibration. Auxiliary slots on the rotor surface can improve the air gap magnetic density sinusoidality by changing the magnetic permeability at different positions of the air gap. The IPM uses a double-layer permanent magnet (PM) rotor structure, and the shape, position, and number of different auxiliary slots affect the torque performance and vibration of the IPM. In this paper, we optimize the rotor auxiliary slot structure of three IPM rotor structures with torque ripple and air gap magnetic density deformation rate (MDDR) as the optimization objectives and summarize the influence of rotor auxiliary slot on the torque performance and vibration of double-layer permanent magnet IPM.

This paper presents an electromagnetic performance analysis method for fast dynamic simulation of a bearingless permanent magnet motor (BPMSM) based on model order reduction (MOR). The electromagnetic characteristics and dynamic behavior model of the rotating machine are constructed by using the MOR based on proper orthogonal decomposition. First, the q-axis and d-axis currents and rotor angle of the motor are scanned to construct the magnetic field distribution snapshot matrix. Then singular value decomposition of the snapshot matrix is used to calculate the basis vectors. Finally, the order of the system is reduced by selecting an appropriate truncation order of the basis vectors. Compared with the finite element method (FEM), the calculation time of MOR for the BPMSM is significantly reduced. At the same time, it can provide accurate results of magnetic field distribution, electromagnetic force, levitation force and dynamic response. Through analysis and comparison, the results of the proposed method match well with the FEM simulations.

With the merits of low power loss, high torque density and high power density, permanent magnet synchronous motors (PMSMs) have been widely applied in various areas. In many applications, the PMSMs are requested to operate with high efficiency over wide speed and load ranges, so the study on proper core loss prediction has attracted much attention for the modeling, design, optimization and control of PMSMs. However, the equivalent circuit model, which is usually applied for motor performance analysis with fast calculation, rarely considers the core loss. This paper presents improved performance analysis of a permanent magnet transverse flux motor with soft magnetic composite stator, based on a modified equivalent circuit model considering core loss. Compared with the experimental measurements on the motor prototype, the performance prediction accuracy based on this new circuit model is much higher than that based on conventional circuit model without core loss.

The digital twin (DT) technique, defined as a dynamic mapping for the physical system to virtual replica, has attracted worldwide attention, which can realize the near real-time interaction among human, machine and environment. This paper aims to present an overview on the research status and technologies of the DT technique and propose an overall DT modeling framework for electrical machines. Among them, property modeling for advanced electrical machine design and analysis is one of the most important research topics which will then be fully investigated. Finally, the key problems that need to be broken through are summarized and the application prospect is also discussed. All the above-mentioned works may trigger in-depth thinking and bring research directions for the application of the DT technique in the field of electrical machines adhering to Industry 4.0 'informatization, digitalization and interaction' concepts.

This paper present a statistical analysis of wind speed data for the Kingdom of Saudi Arabia. The study aim to determine the best probability distribution function for the wind speed data of some selected sites in the Kingdom. This is achieved by analysing a few parameter distribution functions. The probability distribution functions used in the analyses were Weibull, gamma, and Rayleigh distributions. In order to determine the best fits, a mean annual error was used. Results shows that the Weibull distribution has a 0.000601 annual average error, followed by the gamma distribution with an annual error of 0.362221, and finally, the Rayleigh distribution with an annual distribution error 0.63323. This indicates that the sites under study are suitable for electrical power generation in both grid-connected and off-grid modes. Comparing the annual error of each site shows that the gamma distribution performs better compared to other distributions. The results determined the best site for wind speed and very important for various microgrids designs in the Kingdom of Saudi Arabia.

This paper presents a novel application-oriented system level optimization method for switched reluctance motor (SRM) drive systems. First, the multiobjective optimization model is defined according to the design requirements. Then, all the parameters of the motor and controller are divided into three subspaces according to the sensitivity results on the defined objectives. Finally, the optimization of each subspace is performed sequentially by using the approximate models and advanced genetic algorithm, and the best solution can be selected from the Pareto optimal solutions. To verify the effectiveness of the proposed method, an SRM drive system with a segmented-rotor SRM and the angle position control method is investigated. This is a high-dimensional system level optimization problem with ten parameters. The computational cost can be greatly reduced without the sacrifice of accuracy. From the discussion, it can be found that the proposed multiobjective system level optimization method can achieve high efficiency and low torque ripple. Besides, it provides alternative solutions for applications with different output power demands.

Concerns about advantages such as high efficiency and power density, small size and weight as well as fast dynamic response contribute to the increasing industrial applications of high speed permanent magnet machines (HSPMMs). This paper presents a review on the design and analysis technologies for HSPMMs. Specifically, the stator/rotor structures and materials used in HSPMMs are firstly introduced. Then, the calculation models in terms of stator copper loss, stator iron loss, rotor eddy-current loss and air-friction loss are summarized. Because of the non-negligible influences of high working temperature on motor performance, different calculation approaches of HSPMM temperature distribution and rise as well as the cooling methods are compared. Moreover, the research status of HSPMM mechanical characteristics, including the rotor material strength, bearing support and dynamic behaviors, are analyzed, followed by the conclusions and future directions.

A comprehensive review of the literature for the optimum design of microgrid is presented in this paper. This is aim at realistic evaluation of the current status, some existing research problems, and developed a future research topic in the area. Presently, the penetration of microgrid is increasing, ranging from developed to underdeveloped nations. Depending on the application, microgrids could be installed for specific applications, such as community-based and experimental microgrids. Examples of these situations are also highlighted in the paper.

In this paper, an electric vehicle (EV) charging station model at a workplace EV parking lot with energy storage system (ESS) and renewable energy sources (RESs) is proposed. Its economic operation under different operation modes is further explored. By comparing the paid charging mode at different prices with the free charging mode, the results show that although a sufficiently high charging price can obtain higher profit, the free charging model will bring greater profit growth with appropriate RES and ESS size as EVs will used for vehicle-to-grid (V2G) and grid-to-vehicle (G2V) transactions in return.

Concerns about advantages such as high efficiency, high power density, small size, light weight, and fast dynamic response have contributed to the increasing industrial application of high speed permanent magnet machines (HSPMMs). Aiming at the complex power loss situations due to high operating speed and frequency, in this paper, the calculation models of HSPMM in terms of iron loss and copper loss are reviewed based on the thoroughly overview of previous research outcomes. Moreover, the research status and future directions about HSPMM power loss analysis are illustrated, which may provide a strong reference for the design and optimization of electrical drive systems with HSPMMs.

The vibration of electric power device is a serious problem, and is difficult to estimate in its design optimization stage. In this paper, a dynamic magnetostriction model accounting for the dynamic hysteresis behavior is presented by combining the Becker-Doring crystal magnetostriction model and J-A dynamic hysteresis model. The proposed model can correctly describe the physical mechanism of magnetostriction. To compute the vibration of a transformer core, the presented model is incorporated into the finite-element analysis (FEA), and both the Maxwell stress and the magnetostriction are obtained simultaneously. Meanwhile, the vibration of a three-phase transformer prototype is measured to verify the simulation results. It demonstrated that the proposed method was found to adequately predict the vibration of transformer cores.

This paper has carried out a comprehensive review of the reliability analysis of microgrid. Survey papers on grid-connected microgrids have reported. In addition, the most applicable indices used in the reliability analyses of microgrids have been investigated. Different techniques used for coupling microgrids have been reported. In the same vein, a survey of different models used for comprehensive reliability analysis of microgrids is also reported. In a similar passion, the most frequent indices used in the reliability evaluations of microgrid have been defined. Different microgrids existing globally have also been presented in the paper. Finally, some future research topics in the area of this research have been identified.