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design and optimization of Dual-Winding Fault-Tolerant Permanent Magnet Motor

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CES Transactions on Electrical Machines and Systems 2019年第1期3卷 45-53页

作者： Xuefeng Jiang Shaoshuai Wang Qiang Li Yufei Gao Nanjing University of Science and Technology. the M.S degree in School of Automation Nanjing University of Science and Technology Department of Electrical Engineering School of AutomationNanjing University of Science and Technology

To improve the performance of the traditional fault-tolerant permanent magnet(PM)motor,the design and optimal schemes of dual-winding fault-tolerant permanent magnet motor(DWFT-PMM)are proposed and *** order to obtain small cogging torque ripple and inhibiting the short-circuit current,the air gap surface shape of the PM and the anti short-circuits reactance parameters are designed and *** to the actual design requirements of an aircraft electrical actuation system,the parameters,finite element analysis and experimental verification of the DWFT-PMM after optimal design are *** research results show that the optimized DWFT-PMM owns the merits of strong magnetic isolation,physics isolation,inhibiting the short circuit current,small cogging torque ripple and high fault tolerance.

关键词： Dual-winding motor design and optimization fault-tolerance finite element analysis short-circuit fault

Neural Network aided PMSM multi-objective design and optimization for more-electric aircraft applications

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Chinese Journal of Aeronautics 2022年第10期35卷 233-246页

作者： Yuan GAO Tao YANG Serhiy BOZHKO Pat WHEELER Tomislav DRAGICEVIC Chris GERADA Power Electronics Machines and Control GroupUniversity of NottinghamNottingham NG72RDUK Department of Electrical Engineering Technical University of DenmarkKgs.Lyngby 2800Denmark

This study uses the Neural Network(NN)technique to optimize design of surfacemounted Permanent Magnet Synchronous Motors(PMSMs)for More-Electric Aircraft(MEA)*** key role of NN is to provide dedicated correction factors for the analytical PMSM mass and loss estimation within the entire design *** on that,a globally optimal design can be quickly *** the analytical estimation with Finite-Element Analysis(FEA)is the main research target of training the *** analytical formulae serve as the basis of this study,but they are prone to loss accuracy(especially for a large design space)due to their assumptions and *** the help of the trained NNs,the analytical motor model can give an estimation as accurate as the FEA but with super less time during the optimization *** Average Correction Factor(ACF)approach is regarded as the comparison method to demonstrate the excellent performance of the proposed NN ***,a NN aided three-stage-sevenstep optimization methodology is ***,a Pole-10-Slot-12 PMSM case study is given to demonstrate the feasibility and gain of the NN aided multi-objective optimization *** this case,the NN aided analytical model can generate one motor design in 0.04 s while it takes more than 1 min for the used FEA model.

关键词： design and optimization Loss estimation Mean Length per Turn(MLT) More-Electric Aircraft(MEA) Neural Network(NN) Permanent Magnet Synchronous Motor(PMSM)

State-of-art review of the optimization methods to design the configuration of hybrid renewable energy systems (HRESs)

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Frontiers in Energy 2018年第4期12卷 591-622页

作者： Maurizio FACCIO Mauro GAMBERI Marco BORTOLINI Mojtaba NEDAEI Department of Management and Engineering University of PaduaStradellaSan Nicola 336100 VicenzaItaly Department of Industrial Engineering University of BolognaViale del Risorgimento240136BolognaItaly

The current research aims to present an inclusive review of latest research works performed with the aim of improving the efficiency of the hybrid renewable energy systems (HRESs) by employing diverse ranges of the optimization techniques, which aid the designers to achieve the minimum expected total cost, while satisfying the power demand and the reliability. For this purpose, a detailed analysis of the different classification drivers considering the design factors such as the optimization goals, utilized optimization methods, grid type as well as the investigated technology has been conducted. Initial results have indicated that of all optimization goals, load demand parameters including loss of power supply probability (LPSP) and loss of load probability (LLP), cost, sizing (configuration), energy production, and environmental emissions are the most frequent design variables which have been cited the most. Another result of this paper indicates that almost 70% of the research projects have been dedicated toward the optimization of the off-grid applications of the HRESs. Furthermore, it has been demonstrated that, integration of the PV, wind and battery is the most frequent configuration. In the next stage of the paper, a review concerning the sizing methods has also been carried out to outline the most common techniques which are used to configure the components of the HRESs. In this regard, an analysis covering the optimized indicators such as the cost drivers, energy index parameters, load indicators, battery’s state of charge, PV generator area, design parameters such as the LPSP, and the wind power generation to load ratio, has also been performed.

关键词： hybrid renewable energy systems (HRESs) design and optimization environmental pollutions PV array wind turbines (WTs) inverter diesel generator (DG)

Surrogate role of machine learning in motor-drive optimization for more-electric aircraft applications

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Chinese Journal of Aeronautics 2023年第2期36卷 213-228页

作者： Yuan GAO Benjamin CHEONG Serhiy BOZHKO Pat WHEELER Chris GERADA Tao YANG Power Electronics Machines and Control GroupUniversity of NottinghamNottingham NG 72RDUK School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore 639798Singapore

Motor drives form an essential part of the electric compressors,pumps,braking and actuation systems in the More-Electric Aircraft(MEA).In this paper,the application of Machine Learning(ML)in motor-drive design and optimization process is *** general idea of using ML is to train surrogate models for the *** training process is based on sample data collected from detailed simulation or experiment of motor ***,the Surrogate Role(SR)of ML may vary for different *** paper first introduces the principles of ML and then proposes two SRs(direct mapping approach and correction approach)of the ML in a motor-drive optimization *** different cases are given for the method comparison and validation of ML *** first case is using the sample data from experiments to train the ML surrogate *** the second case,the joint-simulation data is utilized for a multi-objective motor-drive optimization *** is found that both surrogate roles of ML can provide a good mapping model for the cases and in the second case,three feasible design schemes of ML are proposed and validated for the two *** the time consumption in optimizaiton,the proposed ML models can give one motor-drive design point up to 0.044 s while it takes more than 1.5 mins for the used simulation-based models.

关键词： Artificial Neural Network(ANN) design and optimization Machine Learning(ML) More-Electric Aircraft(MEA) Motor drive Permanent Magnet Synchronous Motor(PMSM) Search Algorithm Surrogate Algorithm

Dynamic modulation performance of ferroelectric liquid crystal polarization rotators and Mueller matrix polarimeter optimization

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Frontiers of Mechanical Engineering 2020年第2期15卷 256-264页

作者： Song ZHANG Lelun WANG Anze YI Honggang GU Xiuguo CHEN Hao JIANG Shiyuan LIU School of Mechanical Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China

A ferroelectric liquid crystal polarization rotator(FLCPR)has been widely used in polarization measurement due to its fast and stable modulation *** accurate characterization of the modulation performance of FLCPR directly affects the measurement accuracy of the instrument based on liquid crystal *** this study,FLCPR is accurately characterized using a self-developed high-speed Stokes *** linear and weak circular birefringence are observed during modulation processes,and all the optical parameters of FLCPR are dependent on driving voltage.A dual FLCPR-based Mueller matrix polarimeter is designed on the basis of the Stokes *** designed polarimeter combines the advantages of the high modulation frequency of FLCPR and the ultrahigh temporal resolution of the fast polarization measurement system in the Stokes *** optimal configuration of the designed polarizer is predicted in accordance with singular value decomposition.A simulated thickness measurement of a 24 nm standard SiO2 thin film is performed using the optimal *** show that the relative error in thickness measurement caused by using the unsatisfactory modulation characteristics of FLCPR reaches up to−4.34%.This finding demonstrates the importance of the accurate characterization of FLCPR in developing a Mueller matrix polarizer.

关键词： ferroelectric liquid crystal polarization rotator(FLCPR) dual liquid crystal Mueller matrix polarizer design and optimization

A goal-oriented design Method of CO_(2) Power Cycle(CPC)System

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Energy and AI 2023年第1期11卷 138-149页

作者： Qiyao Zuo Xuan Wang Xianyu Zeng Hua Tian Gequn Shu State Key Laboratory of Engines Tianjin UniversityNo.92Weijin RoadNankai DistrictTianjin300072China University of Science and Technology of China Hefei230027China

The CO_(2)power cycle(CPC)system is an efficient and environmentally friendly method for waste heat recovery(WHR).However,the traditional design and optimization process of a CPC system is very complex and *** paper proposes a novel goal-oriented design method based on machine-learning methods for quickly designing an optimized CPC system with given performance *** taking the design of the CO_(2)transcritical power cycle(CTPC)system for internal combustion engines(ICEs)as an ***,the net output power and the total cost of the system prediction models are trained by simulated *** the multiobjective optimization of the system is carried out by using the genetic algorithm coupled with the prediction models,and the optimization results are used to train a classification ***,the given target indicators are input into the classification model for goal-oriented designing and getting the optimal *** results of the goal-oriented design validation show that the goal-oriented design method can design the CTPC system ***,once the classification model is trained,the CTPC system’s future goal-oriented design process only needs to be calculated once,significantly reducing design *** conclusion,the goal-oriented design method based on machine-learning proposed is a novel and promising *** is a technology that combines computer science and energy science and can provide users with a quick and reliable CPC system design method.

关键词： design and optimization CO_(2)power cycle Machine-learning Waste heat recovery Internal combustion engine

Recent advances in the application of computational fluid dynamics in the development of rotary blood pumps

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Medicine in Novel Technology and Devices 2022年第4期16卷 237-249页

作者： Peng Wu Artificial Organ Technology Lab School of Mechanical and Electric EngineeringSoochow UniversitySuzhouJiangsuChina

In recent years,ventricular assist devices(VADs,also known as blood pumps)have gradually entered clinical practice and provide effective treatment for heart failure ***,adverse events related to mechanical blood damage in patients receiving the VAD treatment,were often reported and have become a major concern during the development of VADs,limiting their clinical and economic *** with bench and in-vivo testing,computational fluid dynamics(CFD)is flexible and inexpensive,offering the possibility to predict hemodynamics and mechanical blood damage in a purely numerical ***,CFD has become an important tool for the design,optimization and evaluation of blood *** stringent requirements of blood pumps require high fidelity ***,this article reviews the current state of the art in high-fidelity methodologies for simulating blood flow and blood damage for the development and evaluation of rotary blood pumps;design and optimization methods of rotatory blood pumps using CFD,as well as future challenges.

关键词： Computational fluid dynamics Blood pump Turbulence Hemodynamics Hemolysis Platelet activation Thrombosis design and optimization

Optical Metrology for Aero Structures

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Optical Metrology for Aero Structures