Five-phase Synchronous Reluctance Machines Equipped with a Novel Type of Fractional Slot Winding

Multi-phase machines are so attractive for electrical machine designers because of their valuable advantages such as high reliability and fault tolerant ability.Meanwhile,fractional slot concentrated windings(FSCW)are well known because of short end winding length,simple structure,field weakening sufficiency,fault tolerant capability and higher slot fill factor.The five-phase machines equipped with FSCW,are very good candidates for the purpose of designing motors for high reliable applications,like electric cars,major transporting buses,high speed trains and massive trucks.But,in comparison to the general distributed windings,the FSCWs contain high magnetomotive force(MMF)space harmonic contents,which cause unwanted effects on the machine ability,such as localized iron saturation and core losses.This manuscript introduces several new five-phase fractional slot winding layouts,by the means of slot shifting concept in order to design the new types of synchronous reluctance motors(SynRels).In order to examine the proposed winding’s performances,three sample machines are designed as case studies,and analytical study and finite element analysis(FEA)is used for validation.

Calculation of torque and speed of induction machines under rotor winding faults

Based on the multi-loop method, the rotating torque and speed of theinduction machine are analyzed. The fluctuating components of the torque and speed caused by rotorwinding faults are studied. The models for calculating the fluctuating components are put forward.Simulation and computation results show that the rotor winding faults will cause electromagnetictorque and rotating speed to fluctuate; and fluctuating frequencies are the same and their magnitudewill increase with the rise of the severity of the faults. The load inertia affects the torque andspeed fluctuation, with the increase of inertia, the fluctuation of the torque will rise, while thecorresponding speed fluctuation will obviously decline.

A nonlinear model for aerodynamic configuration of wake behind horizontal-axis wind turbine

Determination of the aerodynamic configuration of wake is the key to analysis and evaluation of the rotor aerodynamic characteristics of a horizontal-axis wind turbine. According to the aerodynamic configuration, the real magnitude and direction of the onflow velocity at the rotor blade can be determined, and subsequently, the aerodynamic force on the rotor can be determined. The commonly employed wake aerodynamic models are of the cylindrical form instead of the actual expanding one. This is because the influence of the radial component of the induced velocity on the wake configuration is neglected. Therefore, this model should be called a "linear model". Using this model means that the induced velocities at the rotor blades and aerodynamic loads on them would be inexact. An approximately accurate approach is proposed in this paper to determine the so-called "nonlinear" wake aerodynamic configuration by means of the potential theory, where the influence of all three coordinate components of the induced velocity on wake aerodynamic configuration is taken into account to obtain a kind of expanding wake that approximately looks like an actual one. First, the rotor aerodynamic model composed of axial (central), bound, and trailing vortexes is established with the help of the finite aspect wing theory. Then, the Biot-Savart formula for the potential flow theory is used to derive a set of integral equations to evaluate the three components of the induced velocity at any point within the wake. The numerical solution to the integral equations is found, and the loci of all elementary trailing vortex filaments behind the rotor are determined thereafter. Finally, to formulate an actual wind turbine rotor, using the nonlinear wake model, the induced velocity everywhere in the wake, especially that at the rotor blade, is obtained in the case of various tip speed ratios and compared with the wake boundary in a neutral atmospheric boundary layer. Hereby, some useful and referential conclusions are offered for the aerodynamic computation and design of the rotor of the horizontal-axis wind turbine.

Overview of the Rectangular Wire Windings AC Electrical Machine

The rectangular wire winding AC electrical machine has drawn extensive attention due to their high slot fill factor,good heat dissipation,strong rigidity and short end-windings,which can be potential candidates for some traction application so as to enhance torque density,improve efficiency,decrease vibration and weaken noise,etc.In this paper,based on the complex process craft and the electromagnetic performance,a comprehensive and systematical overview on the rectangular wire windings AC electrical machine is introduced.According to the process craft,the different type of the rectangular wire windings,the different inserting direction of the rectangular wire windings and the insulation structure have been compared and analyzed.Furthermore,the detailed rectangular wire windings connection is researched and the general design guideline has been concluded.Especially,the performance of rectangular wire windings AC machine has been presented,with emphasis on the measure of improving the bigger AC copper losses at the high speed condition due to the distinguished proximity and skin effects.Finally,the future trend of the rectangular wire windings AC electrical machine is prospected.

Investigation of Influence of Winding Structure on Reliability of Permanent Magnet Machines

Winding is an important part of the electrical machine and plays a key role in reliability.In this paper,the reliability of multiphase winding structure in permanent magnet machines is evaluated based on the Markov model.The mean time to failure is used to compare the reliability of different windings structure.The mean time to failure of multiphase winding is derived in terms of the underlying parameters.The mean time to failure of winding is affected by the number of phases,the winding failure rate,the fault-tolerant mechanism success probability,and the state transition success probability.The influence of the phase number,winding distribution types,multi three-phase structure,and fault-tolerant mechanism success probability on the winding reliability is investigated.The results of reliability analysis lay the foundation for the reliability design of permanent magnet machines.

Development of Special Winding Machine for HT-7U Superconducting Tokamak

A special winding machine with high accuracy has just been developed and applied to the construction of HT-7U Tokamak. It is one of the critical facilities for R & D of HT-7U construction. The machine mainly consists of five parts, including a CICC pay-off spool, a fourroller correcting assembly, a four-roller forming/bending assembly, a continuous winding structure and a CNC control system with three-axis AC servo motors. The facility is used for Cable in Conduit Conductor (CICC) magnet fabrication of HT-7U. The main requirements of the winding machine are: continuous winding to reduce joints inside the coils; pre-forming CICC conductor to avoid winding with tension; suitable for all TF & PF coils of various coil shapes and within the dimension limit; improving the configuration tolerance and the special flatness of the CICC conductor. This paper emphasizes on the design and fabrication of the special winding machine for HT-7U. Some analyses and techniques in winding process for trial D-shape coil are also presented.

Intelligent Winding Machine of Plastic Films for Preventing Both Wrinkles and Slippages

Flexible continuous plastic films are used to produce various products, including optical films and packaging materials, because plastic film is suited to use in mass production manufacturing processes. Generally, the web handling process is applied to convey the plastic film, which is ultimately rewound into a roll using a rewinder. In this case, wrinkles, slippage and other defects may occur if the rewinding conditions are inadequate. In this paper, the authors explain the development of a rewinder system that prevents wound roll defects—primarily starring and telescoping. The system is able to prevent such defects by optimizing the rewinding conditions of tension and nip-load. Based on the optimum design technique, the tension and nip-load are calculated using a 32-bit personal computer. Our experiments have also empirically shown that this rewinder system can prevent roll defects when applying optimized tension and nip-load. Additionally, inexperienced operators can control this system easily.

Short-term wind speed forecasting bias correction in the Hangzhou area of China based on a machine learning model

准确的风速预报具有重要的社会意义.在本研究中,使用名为WSFBC-XGB的XGBoost机器学习模型对中国浙江省杭州市自动气象站的短期风速预报误差进行校正.WSFBC-XGB使用本地数值天气预报系统的产品作为输入.将WSFBC-XGB校正的结果与传统MOS(模型输出统计)方法校正的结果进行了比较.结果表明:WSFBC-XGB预报风速的均方根误差(RMSE)/准确率(ACC)分别比NWP和MOS降低/提高了26.1%和7.64%/35.6%和7.02%;对于90%的站点WSFBC-XGB的RMSE/ACC均小于/高于MOS.此外,采用平均杂质减少法对WSFBC-XGB的可解释性进行分析,以帮助用户增加对模型的信任.结果表明:10米风速(47.35%),10米风的经向分量(12.73%),日循环(9.97%)和1000百帕风的经向分量(7.45%)是前4个最重要的特征.WSFBC-XGB模型将有助于提高短期风速预报的准确性,为大型户外活动提供支持.

Recent Development of Reluctance Machines with Different Winding Configurations,Excitation Methods,and Machine Structures

This paper reviews the performances of some newly developed reluctance machines with different winding configurations,excitation methods,stator and rotor structures,and slot/pole number combinations.Both the double layer conventional(DLC-),double layer mutually-coupled(DLMC),single layer conventional(SLC-),and single layer mutually-coupled(SLMC-),as well as fully-pitched(FP)winding configurations have been considered for both rectangular wave and sinewave excitations.Different conduction angles such as unipolar􀫚120°elec.,unipolar/bipolar􀫚180°elec.,bipolar􀫛240°elec.and bipolar􀫜360°elec.have been adopted and the most appropriate conduction angles have been obtained for the SRMs with different winding configurations.In addition,with appropriate conduction angles,the 12-slot/14-pole SRMs with modular stator structure is found to produce similar average torque,but lower torque ripple and iron loss when compared to non-modular 12-slot/8-pole SRMs.With sinewave excitation,the doubly salient synchronous reluctance machines with the DLMC winding can produce the highest average torque at high currents and achieve the highest peak efficiency as well.In order to compare with the conventional synchronous reluctance machines(SynRMs)having flux barriers inside the rotor,the appropriate rotor topologies to obtain the maximum average torque have been investigated for different winding configurations and slot/pole number combinations.Furthermore,some prototypes have been built with different winding configurations,stator structures,and slot/pole combinations to validate the predictions.

Meshless Surface Wind Speed Field Reconstruction Based on Machine Learning

We propose a novel machine learning approach to reconstruct meshless surface wind speed fields,i.e.,to reconstruct the surface wind speed at any location,based on meteorological background fields and geographical information.The random forest method is selected to develop the machine learning data reconstruction model(MLDRM-RF)for wind speeds over Beijing from 2015-19.We use temporal,geospatial attribute and meteorological background field features as inputs.The wind speed field can be reconstructed at any station in the region not used in the training process to cross-validate model performance.The evaluation considers the spatial distribution of and seasonal variations in the root mean squared error(RMSE)of the reconstructed wind speed field across Beijing.The average RMSE is 1.09 m s^(−1),considerably smaller than the result(1.29 m s^(−1))obtained with inverse distance weighting(IDW)interpolation.Finally,we extract the important feature permutations by the method of mean decrease in impurity(MDI)and discuss the reasonableness of the model prediction results.MLDRM-RF is a reasonable approach with excellent potential for the improved reconstruction of historical surface wind speed fields with arbitrary grid resolutions.Such a model is needed in many wind applications,such as wind energy and aviation safety assessments.

SCADA Data-Based Support Vector Machine for False Alarm Identification for Wind Turbine Management

Maintenance operations have a critical influence on power gen-eration by wind turbines(WT).Advanced algorithms must analyze large volume of data from condition monitoring systems(CMS)to determine the actual working conditions and avoid false alarms.This paper proposes different support vector machine(SVM)algorithms for the prediction and detection of false alarms.K-Fold cross-validation(CV)is applied to evaluate the classification reliability of these algorithms.Supervisory Control and Data Acquisition(SCADA)data from an operating WT are applied to test the proposed approach.The results from the quadratic SVM showed an accuracy rate of 98.6%.Misclassifications from the confusion matrix,alarm log and maintenance records are analyzed to obtain quantitative information and determine if it is a false alarm.The classifier reduces the number of false alarms called misclassifications by 25%.These results demonstrate that the proposed approach presents high reliability and accuracy in false alarm identification.

A data-driven machine learning approach for yaw control applications of wind farms

This study proposes a cost-effective machine-learning based model for predicting velocity and turbulence kineticenergy fields in the wake of wind turbines for yaw control applications.The model consists of an auto-encoderconvolutional neural network(ACNN)trained to extract the features of turbine wakes using instantaneous datafrom large-eddy simulation(LES).The proposed framework is demonstrated by applying it to the Sandia NationalLaboratory Scaled Wind Farm Technology facility consisting of three 225 kW turbines.LES of this site is performedfor different wind speeds and yaw angles to generate datasets for training and validating the proposed ACNN.It is shown that the ACNN accurately predicts turbine wake characteristics for cases with turbine yaw angleand wind speed that were not part of the training process.Specifically,the ACNN is shown to reproduce thewake redirection of the upstream turbine and the secondary wake steering of the downstream turbine accurately.Compared to the brute-force LES,the ACNN developed herein is shown to reduce the overall computational costrequired to obtain the steady state first and second-order statistics of the wind farm by about 85%.

Application of four machine-learning methods to predict short-horizon wind energy

Renewable energy has garnered attention due to the need for sustainable energy sources.Wind power has emerged as an alternative that has contributed to the transition towards cleaner energy.As the importance of wind energy grows,it can be crucial to provide forecasts that optimize its performance potential.Artificial intelligence(AI)methods have risen in prominence due to how well they can handle complicated systems while enhancing the accuracy of prediction.This study explored the area of AI to predict wind-energy production at a wind farm in Yalova,Turkey,using four different AI approaches:support vector machines(SVMs),decision trees,adaptive neuro-fuzzy inference systems(ANFIS)and artificial neural networks(ANNs).Wind speed and direction were considered as essential input parameters,with wind energy as the target parameter,and models are thoroughly evaluated using metrics such as the mean absolute percentage error(MAPE),coefficient of determination(R~2),and mean absolute error(MAE).The findings accentuate the superior performance of the SVM,which delivered the lowest MAPE(2.42%),the highest R~2(0.95),and the lowest MAE(71.21%)compared with actual values,while ANFIS was less effective in this context.The main aim of this comparative analysis was to rank the models to move to the next step in improving the least efficient methods by combining them with optimization algorithms,such as metaheuristic algorithms.

Multi-model ensemble forecasting of 10-m wind speed over eastern China based on machine learning optimization

风对人类活动和电力运行有重大影响,准确预报短期风速具有深远的社会和经济意义.基于中国东部100个站点,本研究首先评估了5个业务模式对10米风速的预报能力,日本气象厅JMA模式在减少预报误差方面表现最好.进一步,利用5种数值模式和多种机器学习方法,将动力和统计相结合,对每个站点分别进行了特征工程和机器学习算法优选,建立了10米风速多模式集成预报模型。针对24至96小时预报时长,将该方法的预报性能与基于岭回归的多模式集成和JMA单模式进行比较.结果表明,基于机器学习优选的多模型集成方法可以将JMA模式的预报误差降低39%以上,预报效果的提升在11月最明显.此外,该方法优于基于岭回归的多模式集成方法.

Inductances Estimation in the d-q Axis for an Interior Permanent-Magnet Synchronous Machines with Distributed Windings

The inductances in d-q axis have an important influence on the behavior of PMSM （PM （permanent-magnet） synchronous machines）. Their calculation is fundamental not only to evaluate the performance such as torque and field weakening capability but also to design the control system to maximize performance and power factor. This paper presents a study of inductance in the d-q axis for buried （i.e., IPMSM （interior） PM Synchronous Machines）. This study is achieved using 2-D （two-dimensional） FEM （finite-element method） and Park＇s transformation.

Direct Power Control of Variable Wind Speed Based on the Doubly Fed Asynchronous Machine

In this work, the authors propose the study of a wind speed variable based on the DFAM （double fed asynchronous machine）. The model of the turbine is drawn from the classical equations describing the operation of a variable wind speed. The torque generated by the turbine is applied to the DFAM directly connected on the network side and the stator via a bidirectional converter side rotor. This configuration allows velocity variations of ±30% around the synchronous speed and the converter is then sized to one third of the rated power of the machine. The DFAM is controlled by a control vector ensuring operation of the wind turbine power coefficient maximum.

Limit Requirements Simulation of Sundial Solar Tracking Machine

Sundial solar tracking machines are machines that tracking the sun,and can promote sunshine receiving efficiency of solar panels.Their operations are strongly influenced by wind load.Previous studies were focused on tracking accuracy and tracking methods,the influence of wind load to the operation of the tracking machines has not caused enough attention,so that many tracking machines did not have the reasonable design basis,which led to unreasonable design and high maintenance costs,and had seriously influenced the application and popularization of the tracking machines.Therefore,the 16 m2 sundial solar tracking machine is taken as research object from the perspective of wind load.A series of computational fluid dynamics（CFD） analyses are carried out on the model of the 16 m2 sundial solar tracking machine.Firstly,in order to make CFD analyses carry on smoothly,after the three-dimensional solid model is established,the model is simplified,and grids are meshed on the simplified model.Then,in the virtual environment,to make the simulation closer to real but at the same time not too complex to make simulation hard to realize,assumptions of the nature of air flow are conducted,boundary conditions of the analyses are set reasonably,and appropriate CFD analysis solver is also chosen.Finally,the results of the CFD analyses are also analyzed and sorted;and limit requirements（i.e.,force conditions of limit case）,such as the maximum load and the maximum total torque,are provided for the further finite element analyses（FEA） and the optimization design of the products.This paper presents an effective computer simulation analysis method for the design and optimization of this type of solar tracking machine,and this method can greatly shorten the development cycle and cost.

Design and Performance Analysis of Axial Flux Permanent Magnet Machines with Double-Stator Dislocation Using a Combined Wye-Delta Connection

Conventional fractional slot concentrated winding three-phase axial flux permanent magnet machines have an abundance of armature reaction magnetic field harmonics which deteriorate the torque performance of the machine.This paper presents a double-stator dislocated axial flux permanent magnet machine with combined wye-delta winding.A wye-delta(Y-△)winding connection method is designed to eliminate the 6 th ripple torque generated by air gap magnetic field harmonics.Then,the accurate subdomain method is adopted to acquire the no-load and armature magnetic fields of the machine,respectively,and the magnetic field harmonics and torque performance of the designed machine are analyzed.Finally,a 6 k W,4000 r/min,18-slot/16-pole axial flux permanent magnet machine is designed.The finite element simulation results show that the proposed machine can effectively eliminate the 6 th ripple torque and greatly reduce the torque ripple while the average torque is essentially identical to that of the conventional three-phase machines with wye-winding connection.

Modularity Techniques in High Performance Permanent Magnet Machines and Applications

This paper reviews the modularity techniques in the stator manufacture of permanent magnet machines for different applications.Some basic concepts of modular machines are firstly introduced.Modular machines for several typical applications are then described in details,including domestic appliances,automobiles and electric vehicles,more electric aircrafts and civic applications,wind power generators,etc.Besides,the influence of manufacture tolerance gaps and flux barriers on the electromagnetic performance is discussed.