Relevant bibliographies by topics / Electrical machine design and optimization

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
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Academic literature on the topic 'Electrical machine design and optimization'

Author: Grafiati
Published: 9 March 2023
Last updated: 10 March 2023

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Journal articles on the topic "Electrical machine design and optimization"

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Müller, Samuel, David Maier, and Nejila Parspour. "Inductive Electrically Excited Synchronous Machine for Electrical Vehicles—Design, Optimization and Measurement." Energies 16, no. 4 (February 7, 2023): 1657. http://dx.doi.org/10.3390/en16041657.

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The demand for electric machines has been rising steadily for several years—mainly due to the move away from the combustion engine. Synchronous motors with rare earth permanent magnets are widely used due to their high power densities. These magnets are cost-intensive, cost-sensitive and often environmentally harmful. In addition to dispensing with permanent magnets, electrically excited synchronous machines offer the advantage of an adjustable excitation and, thus, a higher efficiency in the partial load range in field weakening operation. Field weakening operation is relevant for the application of vehicle traction drive. The challenge of this machine type is the need for an electrical power transfer system, usually achieved with slip rings. Slip rings wear out, generate dust and are limited in power density and maximum speed due to vibrations. This article addresses an electrically excited synchronous machine with a wireless power transfer onto the rotor. From the outset, the machine is designed with a wireless power transfer system for use in a medium-sized electric vehicle. As an example, the requirements are derived from the BMW’s i3. The wireless power transfer system is integrated into the hollow shaft of the rotor. Unused space is thus utilized. The overall system is optimized for high efficiency, especially for partial load at medium speed, with an operation point-depending optimization method. The results are compared with the reference permanent magnet excited machine. A prototype of the machine is built and measured on the test bench. The measured efficiency of the inductive electrically excited synchronous machine is up to 4% higher than that of the reference machine of the BMW i3.
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Nell, Martin, Alexander Kubin, and Kay Hameyer. "Multi-Stage Optimization of Induction Machines Using Methods for Model and Parameter Selection." Energies 14, no. 17 (September 4, 2021): 5537. http://dx.doi.org/10.3390/en14175537.

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Optimization methods are increasingly used for the design process of electrical machines. The quality of the optimization result and the necessary simulation effort depend on the optimization methods, machine models and optimization parameters used. This paper presents a multi-stage optimization environment for the design optimization of induction machines. It uses the strategies of simulated annealing, evolution strategy and pattern search. Artificial neural networks are used to reduce the solution effort of the optimization. The selection of the electromagnetic machine model is made in each optimization stage using a methodical model selection approach. The selection of the optimization parameters is realized by a methodical parameter selection approach. The optimization environment is applied on the basis of an optimization for the design of an electric traction machine using the example of an induction machine and its suitability for the design of a machine is verified by a comparison with a reference machine.
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Torres, Jorge, Pablo Moreno-Torres, Gustavo Navarro, Marcos Blanco, Jorge Nájera, Miguel Santos-Herran, and Marcos Lafoz. "Asymmetrical Rotor Skewing Optimization in Switched Reluctance Machines Using Differential Evolutionary Algorithm." Energies 14, no. 11 (May 29, 2021): 3194. http://dx.doi.org/10.3390/en14113194.

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Minimizing torque ripple in electrical machines for a given application is not a straightforward task, especially when the application imposes certain constraints. There are many techniques to improve torque ripple, either design-based or control-based. In this paper, a new geometry for switched reluctance machines based on rotor poles skewing is proposed to minimize torque ripple. This paper describes a methodology to design an asymmetrical skew rotor—switched reluctance machine using a multi-objective differential evolutionary algorithm. The main parameters of the optimization process are defined, as is the optimization methodology to obtain an improved design with less torque ripple than a conventional one. Moreover, the analytical formulas used in the optimization method, as well as the optimization technique, are deduced and explained in detail. The mathematical model used to simulate the electrical machine and the power converter are also described. Two-dimensional and three-dimensional finite element analyses were also conducted to assess whether 3D effects (end-effect and axial fringing field) affected the results. Finally, a particular case of a high-voltage direct current-controlled generator in the base of the More Electric Aircraft (MEA) concept or an energy storage system as an electrical machine was analyzed, and the results for the improved configuration were compared with those for the conventional one.
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Pham, Thang, Patrick Kwon, and Shanelle Foster. "Additive Manufacturing and Topology Optimization of Magnetic Materials for Electrical Machines—A Review." Energies 14, no. 2 (January 6, 2021): 283. http://dx.doi.org/10.3390/en14020283.

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Additive manufacturing has many advantages over traditional manufacturing methods and has been increasingly used in medical, aerospace, and automotive applications. The flexibility of additive manufacturing technologies to fabricate complex geometries from copper, polymer, and ferrous materials presents unique opportunities for new design concepts and improved machine power density without significantly increasing production and prototyping cost. Topology optimization investigates the optimal distribution of single or multiple materials within a defined design space, and can lead to unique geometries not realizable with conventional optimization techniques. As an enabling technology, additive manufacturing provides an opportunity for machine designers to overcome the current manufacturing limitation that inhibit adoption of topology optimization. Successful integration of additive manufacturing and topology optimization for fabricating magnetic components for electrical machines can enable new tools for electrical machine designers. This article presents a comprehensive review of the latest achievements in the application of additive manufacturing, topology optimization, and their integration for electrical machines and their magnetic components.
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Zaaraoui, Lassaad, and Ali Mansouri. "Optimization and finite element analysis of an in-wheel permanent magnet motor." Malaysian Journal of Fundamental and Applied Sciences 17, no. 1 (February 27, 2021): 104–8. http://dx.doi.org/10.11113/mjfas.v17n1.1981.

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Nowadays, artificial intelligence techniques have become widely used in electrical machines optimization and design. In this attempt, different methods have been proposed. The present work is devoted to the electromagnetic analysis and design of an in-wheel radial flux outer rotor surface mounted permanent magnet motor (SMPM) for electric vehicle application. Two based-Swarm Particle Optimization (PSO) techniques, namely, the improved PSO multi-Objective optimization and the Speed-constrained Multi-objective PSO Optimization, are applied. The main idea of the current optimization procedure is to determine the optimal machine sizing parameters providing the maximum of efficiency with the minimum of weight. To reach this goal, two objective functions are employed the efficiency maximization and the weight minimization. A preliminary analytical model describing the magnetic and electrical machine features was presented. In order to find the optimum design, the optimization results are discussed and analyzed. In addition, the electromagnetic performances of the found optimum design were studied by means of finite element analysis (FEA) and compared with those obtained by the optimization procedure.
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Lu, Meng, Gabriel Domingues-Olavarría, Francisco J. Márquez-Fernández, Pontus Fyhr, and Mats Alaküla. "Electric Drivetrain Optimization for a Commercial Fleet with Different Degrees of Electrical Machine Commonality." Energies 14, no. 11 (May 21, 2021): 2989. http://dx.doi.org/10.3390/en14112989.

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At present, the prevalence of electric vehicles is increasing continuously. In particular, there are promising applications for commercial vehicles transferring from conventional to full electric, due to lower operating costs and stricter emission regulations. Thus, cost analysis from the fleet perspective becomes important. The study of cost competitiveness of different drivetrain designs is necessary to evaluate the fleet cost variance for different degrees of electrical machine commonality. This paper presents a methodology to find a preliminary powertrain design that minimizes the Total Cost of Ownership (TCO) for an entire fleet of electric commercial vehicles while fulfilling the performance requirements of each vehicle type. This methodology is based on scalable electric machine models, and particle swarm is used as the main optimization algorithm. The results show that the total cost penalty incurred when sharing the same electrical machine is small, therefore, there is a cost saving potential in higher degrees of electrical machine commonality.
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Shaitor, Nikolay, Michal Kelemen, and Boris Yakimovich. "Analysis and Synthesis in the Design of Magnetic Switching Electric Machines." Actuators 10, no. 7 (July 16, 2021): 164. http://dx.doi.org/10.3390/act10070164.

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A systematic approach to the design of electrical machines is implemented by solving problems of analysis and synthesis in various combinations at different stages and stages of design. The questions of the formulation and implementation of synthesis and analysis problems in the study and design of modular-type magnetically commutated electrical machines are considered. They are aimed at reducing weight, size and cost while improving the performance of these newly designed machines. A complex method of parametric synthesis and an automated program containing a calculated mathematical model of an electric machine has been developed. On the basis of numerical full factorial experiments, the optimization parameter is determined, and a regression analysis is performed with the construction of an optimization model. It allows you to find a narrow range of variation of significant factors, at which the optimization parameter satisfies the specified conditions. On the example of studying an inductor generator of axial-radial configuration, new approaches to the formulation and solution of typical problems of analysis and synthesis of modular-type electrical machines are shown. The use of complex parametric synthesis makes it possible to significantly reduce the masses of the designed modular machines in comparison with drum-type inductor machines of the same power.
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Zhao, Yao, Chuanyang Lu, Dongdong Li, Xing Zhao, and Fan Yang. "Overview of the Optimal Design of the Electrically Excited Doubly Salient Variable Reluctance Machine." Energies 15, no. 1 (December 30, 2021): 228. http://dx.doi.org/10.3390/en15010228.

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The Electrically Excited Doubly Salient Variable Reluctance Machine (EEDSVRM) is a new type of brushless machine designed according to the principle of air gap reluctance change. There is neither permanent magnet steel nor excitation winding on the rotor. The rotor is made of silicon steel sheets, thus the structure of the variable reluctance machine is very simple. There are many optimization methods for this type of machine optimal design, such as novel machine topology optimization, finite element simulation-based optimization, mathematical analysis-based optimization, intelligent algorithm-based optimization, and multiple fusion-based optimization. Firstly, this article introduces the basic structure and working principle of the EEDSVRM and analyzes both its common regularity and individual difference. Then, the different optimization design methods of EEDSVRM are reviewed, the advantages and disadvantages of the different optimization methods are summarized, and the research interests of the optimization design of variable reluctance machines in the future are prospected.
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Fodorean, Daniel, and Lorand Szabo. "Study of Permanent Magnet Synchronous Machine Topologies for Electric Scooter Application." Advanced Engineering Forum 8-9 (June 2013): 397–404. http://dx.doi.org/10.4028/www.scientific.net/aef.8-9.397.

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The paper deals with the study of the motorization for an electric scooter. The motivation of this study is firstly introduced. Next, the application is defined: it is intended to propose a pure electrical traction system for a light electric vehicle, meaning an electric scooter). A short description of the design will introduce the main parameters of the electrical drive system and three topologies of electrical machine will be evaluated. The optimization of the best suited variant will be made based on a gradient type optimization algorithm. Numerical computation, by means of finite element method, will confirm the analytical obtained results, emphasizing the main achievements, performances and drawbacks of the electrical traction system. These performances are evaluated on test bench for validation.
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Shuraiji, Ahlam Luaibi, and M. M. J. Al-ani. "Design and optimization of HTS flux-switching permanent magnet machine." International Journal of Power Electronics and Drive Systems (IJPEDS) 10, no. 4 (December 1, 2019): 1751. http://dx.doi.org/10.11591/ijpeds.v10.i4.pp1751-1757.

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<p>Flux-switching permanent magnet (FSPM) machine with high temperature superconductors (HTS) bulks located between the rotor poles to eliminate the flux leakage in the rotor, termed as (HTS-FSPM) machine has been proposed in this paper. Using genetic algorithm, the HTS and the conventional FSPM machines having the same size constraints and load conditions have been globally optimized for max. aveage torque. To highlight the advantages of the HTS-FSPM machine, a performance comparison between the conventional and HTS-FSPM machines has been presented. It is found that the HTS-FSPM machine can increase the torque by 27%, however, this comes with the expense of higher torque ripple and power losses. </p>
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Dissertations / Theses on the topic "Electrical machine design and optimization"

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Vadamodala, Lavanya. "Reliability Based Multi-Objective Design Optimization for Switched Reluctance Machines." University of Akron / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=akron162033146640203.

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Degano, Michele. "Analysis, Design and Optimization of Innovative Electrical Machines Using Analytical and Finite Element Analysis Methods." Doctoral thesis, Università degli studi di Padova, 2015. http://hdl.handle.net/11577/3424147.

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The interest on rotating electrical machines adopting permanent magnets (PMs) has increased during the past few decades, representing now a fashionable design option in a number of fields as industrial processing, transportation, actuators, household appliances and power plants. The issues related to an increasing electrical energy demand and consumption, have generated a tendency to research electrical drives with high efficiency, pushing electrical machines technology to further improvements. The introduction of permanent magnets based on rare earth, experienced since the 1960's, gave a great input in the development of innovative machine topologies. On the other hand, the increase and the instability of rare earth PMs price, especially between 2010 and 2013, have directed the research of rare earth free alternatives, or machines using a smaller amount of PMs. Actually, the current trend in the industrial and academic research focused on developing high performance electric motors and generators, among different electrical machines, highlights the Synchronous Reluctance (SynRel) and the Permanent Magnet Synchronous Reluctance (PMASynRel) motors as best candidates to satisfy the future energy and efficiency requirements. This thesis is comprehensively dedicated to theoretical and experimental analysis and design of the Synchronous Reluctance (SynRel) and the Permanent Magnet Assisted Synchronous Reluctance (PMASynRel) machines. In particular, it will be focused on electrical machines which power ratings are ranging from fraction of Watts to some hundred kWatts, for vehicular traction and house-hold appliances. SynRel and PMASynRel motors exhibit many technical advantages, like simple and robust structure, high torque density, high efficiency, small space required for PMs, high degrees of freedom in the design, high operating speed range, high overload capability, low back EMF (null in case of SynRel motors), leading to a safe behavior in case of inverter failure. Furthermore, thanks to the appropriate vector control algorithm, the performance in terms of efficiency and torque become highly competitive. The subject matter covered in the thesis is organized into three Parts, each including a certain number of chapters. % At the beginning of each Part, a brief summary is proposed aiming to describe the main content of that Part, the goals and the anticipation of the main results. Part I includes seven chapters summarizing the research activities carried out during the Ph.D. period. The first six chapters are dedicated to electrical machines for vehicular traction, while chapter 7 investigate on motors for house-hold appliances. Chapter 1 is mainly introductory and meant to provide the basics information to understand which are the pros and cons and the features of the machines under study. Chapter 2 summarize the design criteria and the electrical requirements of ferrite PMASynRel machine for traction application. The electromechanical performance have been evaluated and compared, in terms of torque and power. A brief description of the electric supply system in order to accurately and efficiently manage the motor for achieving the requested performance is presented. Chapter 3 highlights the influence and benefits of using ferrite magnets on the machine performance, emphasizing the importance of a careful evaluation of the magnet volume in order to increase the performance while reducing the used quantity. Chapter 4 is devoted to the sensitivity analysis of the machine performance in terms of torque ripple with respect to the geometrical design. An optimization algorithm has been performed in order to investigate and determine a rotor geometry which maximize the torque and reduces the torque ripple. The impact of the geometrical parameters is taken into account and the sensitivity of the optimal solution to the geometry variation is pointed out. This chapter highlights the difficulty to get a robust geometry as far as the torque ripple reduction is concerned. Finally, a few experimental results on a Synchronous Reluctance motor prototype will be presented, compared with Finite Element Analysis simulations for validation. Chapter 5 deals with the design and optimization of a high speed PMASynRel motor considering the driving cycles of an electric vehicle. A procedure is employed to evaluate the most effective design area, which has to be considered for the global optimization. Both results and advantages of the adopted methodology are highlighted. Further analysis on traction machines are going to be presented in Chapter 6. A comparison between ferrite and sintered NdFeB PMASynRel, SynRel and a Surface mounted PM (SPM) machines performance is deeply investigated. Chapter 7, the last of this first part, will highlight the advantages in using SynRel and PMASynRel motors for house-hold appliances. The main purpose of this chapter is to discuss the features of these motors as a valid substitute to commercial motors actually used for washing machines application. Part II is dedicated to the analytical modeling of SynRel machines with the challenge of predicting accurately the air-gap field of the machine taking into account the effect of the rotor flux barriers. This Part is divided into two chapters. Chapter 8 explains the hypothesis on which the analytical model is based, the calculation of stator Magneto Motive Force through winding function and describes the reluctance network equivalent circuit for a SynRel motor with one and two flux barriers per pole. The computation of the parameters of the model, the air-gap flux density and finally some comparison with Finite Element Analysis are presented. In Chapter 9 SynRel motors with split-phase stator winding sets supplied by multiple inverters have been investigated as an increasingly attractive solution for fault-tolerant, rugged, magnet-free vehicle traction drives. As an extension to the previous chapter, an analytical procedure to model and simulate a SynRel motor, with a split-phase stator winding, through a magnetic equivalent circuit (MEC) technique, has been introduced. As an output, the air-gap flux density of the SynRel motor can be computed at any operating point. Part III, finally, presents some experimental measurements carried out for two prototypes of SynRel and PMASynRel machines, with the purpose of comparing the results achieved in the motor optimization presented in Chapter 7.
In questi ultimi anni l’interesse per le macchine elettriche rotanti facenti uso di magneti permanenti ha riscontrato uno sviluppo sempre pi `u crescente. Tali macchine rappresentano un mondo alternativo alle tradizionali macchine sincrone e ad induzione, e vengono considerate ad oggi soluzioni promettenti in svariati settori, come quello industriale, per il trasporto, come attuatori, elettro domestici e per l’impiego in impianti di potenza. I problemi legati all aumento della domanda di energia elettrica ed al suo consumo, hanno generato una tendenza alla ricerca di azionamenti ad alta efficienza, spingendo la tecnologia delle macchine elettriche classiche ad ulteriori miglioramenti. L’introduzione dei magneti permanenti che utilizzano terre rare, gia dagli anni 60, hanno incentivato e permesso lo sviluppo di diversi tipi di macchina innovativi. Tuttavia, l’aumento e l’instabilita del prezzo delle terre rare, tra il 2010 ed il 2013, ha diretto la ricerca verso soluzioni di macchine alternative senza magneti permanenti, o con una quantita ridotta di tali materiali, pur soddisfando le specifiche di progetto. Al momento, la ricerca industriale e quella accademica sono entrambe focalizzate allo sviluppo di motori e generatori elettrici con elevate prestazioni, tra i diversi tipi di macchine elettriche esistenti, i motori sincroni a riluttanza (SynRel) ed a riluttanza assistita da magneti permanenti (PMASynRel) risultano essere degli ottimi candidati per il soddisfacimento delle specifiche energetiche e di efficienza, sempre piu stringenti, che verranno richieste ai motori nel prossimo futuro. Questo lavoro di tesi e interamente dedicato all’analisi teorica e sperimentale ed alla progettazione di motori sincroni a riluttanza (SynRel) e motori sincroni a riluttanza assistita da magneti permanenti (PMASynRel). In particolare, l’attenzione sar`a p osta su macchine elettriche in un campo di potenza che varia dalle centinaia di Watt alle decinedi kiloWatt, principalmente per applicazioni come veicoli elettrici ed elettro domestici. Tali macchine presentano una serie di vantaggi tecnologici che le portano ad avere prestazioni, soprattutto nel campo degli azionamenti a velo cit`a variabile (VSD), competitive rispetto ad esempio alle macchine ad induzione tradizionali o quelle a magneti permanenti. La struttura semplice e robusta, l’utilizzo ridotto di magneti permanenti, i gradi di liberta nella progettazione combinate ad un’elevata densita di coppia, alta efficienza elevate caratteristiche di sovraccarico ed un ampio campo di velocita, sono tutte caratteristiche che hanno permesso di collo care le macchine SynRel e PMASynRel in una posizione di rilievo. Inoltre, grazie all’aumento dei convertitori moderni a frequenza variabile e sistemi di controllo digitale, le prestazioni di questo tip o di motori, in termini di coppia ed efficienza, sono diventate altamente competitive rispetto ai tradizionali azionamenti con motori ad induzione.
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Angle, Matthew G. (Matthew Gates). "Modeling, design, and optimization of permanent magnet synchronous machines." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/103662.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 283-285).
Improvement of performance of robots has necessitated technological advances in control algorithms, mechanical structures, and electric machines. Running, legged robots have presented challenges in the area of electric machinery in particular. In addition to the low-speed, high-torque, low-mass requirements on the machines, the act of running results in an unconventional drive cycle that consists of brief periods of high torque followed by long stretches of minimal torque requirement, a performance envelope that is not matched by commercially-available machines. An optimized motor would dissipate the minimum possible power over the given drive cycle, lowering temperatures and potentially reducing required battery mass or extending range. These performance requirements have motivated faster modeling techniques to enable optimization of designs for these unconventional applications. This thesis presents a novel, fast modeling method for permanent magnet synchronous machines consisting of a hybrid model comprising an explicit Maxwell solution and a Flux Tube solution. The Maxwell solution is performed for the rotor and airgap of the machine, where geometries are simple and materials are homogeneous. The stator, with its geometric complexities and non-linear materials, is modeled with a lumped-parameter model based on ux tubes. The two models are then stitched together, forced to be self-consistent with boundary conditions, and allowed to converge. This captures effects such as cogging torque as well as saturation of the core materials. The method is approximately four orders of magnitude faster than a reference finite element program (0.01 s versus 100 s) for the same accuracy. The modeling method is implemented for two topologies of surface-mount permanent-magnet machines, an internal-rotor machine and an external-rotor machine. It is then used to optimize machine design to a given drive cycle, including effects of core loss. A machine is built to demonstrate the validity of the model and optimization method and test results match predictions of instantaneous torque to within 5% at the worst point. Cogging torque is another aspect of performance that is important to machines for robotics and other applications. These pulsations in torque caused by magnet alignment with geometric features in the stator result in undesired vibrations and issues with control. One method, based on skew, for reducing or eliminating cogging torque is explored, and a simple analytical technique to predict the eect of skew is presented. Based on the machine optimized for the Cheetah, two additional machines were built to explore the effects of cogging: a skewed-rotor machine, and a skewed- stator machine. Each demonstrated reduction of a particular cogging harmonic or all of the cogging. The skewed machines reduced cogging by approximately 85%. Novel magnet shapes which further reduce cogging are presented and finite element modeling suggests that they can further reduce cogging by 60% over a straight skew. The design and optimization tools developed herein and described above were used to optimize a motor for the MIT Cheetah Robot. The resulting motor showed nearly an order of magnitude increase in torque density when compared to commercial, off-the-shelf machines (1.3 kg vs 820 g and 10 Nm vs 28 Nm) with simultaneous improvements to efficiency.
by Matthew G. Angle.
Ph. D.
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Wang, Ziyu S. M. Massachusetts Institute of Technology. "Loss pattern recognition and profitability prediction for insurers through machine learning." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/111514.

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Thesis: S.M., Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2017.
S.M. !c Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science 2017
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 91-94).
For an insurance company, assessing risk exposure for Property Damage (PD), and Business Interruption (BI) for large commercial clients is difficult because of the heterogeneity of that exposure, within a single client (account), and between different divisions, and regions, where the client is active. Traditional risk assessment models attempt to scale up the single location approach used in personal lines: A large amount of data is collected to profile a sample of the locations and based on this information the risk is then inferred and somewhat subjectively assessed for the whole account. The assumption is that the risk characteristics at the largest locations are representative of all locations, and moreover, that risk is proportional to the size of the location. This approach is both ineffective and inefficient. Thus our first goal is to build a better risk assessment model through machine learning based on clients' data from internal sources. Further, we define a new problem, to predict whether a specific contract would be profitable or unprofitable for the insurance company. This problem turns out to be an imbalance classification, which attracts the second half of our research efforts in this thesis. In Chapter 2, we first review related literature on state-of-the-art risk assessment models in the field of insurance. Later in the chapter we move to the imbalance classification problems and review some popular and effective solutions researchers have proposed. In Chapter 3, we describe the data structure, provide some preliminary analysis over certain attributes and discuss the preprocessing techniques used for feature construction. In Chapter 4, we propose a new model with the objective to develop a new risk index which represents clients' potential future risk level. We then compare the performance of our new index with the original risk index used by the insurance company and computational results show that our new index successfully captures clients' financial loss pattern, while the original risk score used by the insurance company fails to do so. In Chapter 5, we propose a multi-layer algorithm to predict whether a specific contract would be profitable or unprofitable for the insurance company. Simulation shows that we can accurately label more than 83 percent of the contracts on record and that our proposed algorithm outperforms traditional classifiers such as Support Vector Machines and Random Forests. Later in the chapter, we define a new imbalance classification problem and propose a hybrid method to improve the recall percentage and prediction accuracy of Support Vector Machines. The method incorporates unsupervised learning techniques into the classical Support Vector Machines algorithm and achieves satisfying results. In Chapter 6, we conclude the thesis and provide future research guidance. This thesis builds models and trains algorithms based on real world business data from a global leading insurance and reinsurance company.
by Ziyu Wang.
S.M.
S.M. !c Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
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Dotz, Boris [Verfasser]. "Windings, Design and Optimization of Electrical Machines for Hybrid Traction Applications / Boris Dotz." Aachen : Shaker, 2018. http://d-nb.info/1188549839/34.

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Duan, Yao. "Method for design and optimization of surface mount permanent magnet machines and induction machines." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/37280.

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Advances in electrical machinery with high efficiencies could significantly reduce the cost of industrial and residential energy systems, thereby reducing fossil fuel needs and emissions. Electrical machine design is a comprehensive process based on several factors, including economic factors, material limitations, specifications and special application-dependent factors. At the same time, machine design is a multi-physics task comprising of electric design, magnetic design, insulation design, thermal design and mechanical design. However, the out-of-date conventional machine design can neither reflect the advances in the past 30 years, nor exploit the trade-offs between design factors from the multi-physics nature of the electrical machine. This work focus on the development a fast and efficient method for the design and optimization of Surface Mount Permanent Magnet (SMPM) machines and induction machines, as influenced by the energy source, mechanical loads, thermal effects, and the up-to-date developments in materials and manufacturing capabilities. A new analytical design method is developed for the electromagnetic design of SMPM machines. Both distributed and concentrated winding types of SMPM machines are considered and compared. Based on the proposed electromagnetic analytical design method and a generic thermo-mechanical machine design model [1], an innovative and computationally efficient electromagnetic-thermo-mechanical integrated design method is developed for SMPM machines. Particle Swarm Optimization (PSO) is applied in a novel way based on this integrated design method for the multi-objective design optimization of SMPM machines. With the proposed method, the thermal and mechanical design is no longer treated separately and heuristically as in the traditional design, but has been systemically integrated with the electromagnetic design; the effect of power source, cooling capability, thermal limits, and up-to-date material capabilities are also reflected in the design and optimization. Superior designs compared to traditional designs can be achieved with PSO based multi-objective optimization. The proposed integrated design approach also has the merit of good computational efficiency and provides a significant time reduction of the design cycle compared to finite element analysis. A novel electromagnetic analytical design method of induction machines has been developed, which needs only six prime design variables but is able to design induction machines in fine details. The advantage over the traditional and other existing design method is that this proposed method does not have the heuristic selection of the design variables and does not need manual design iterations. The computing time is almost negligible and the design cycle is significantly reduced compared to the tradition machine design.
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Sarikhani, Ali. "Design Optimization of Modern Machine-drive Systems for Maximum Fault Tolerant and Optimal Operation." FIU Digital Commons, 2012. http://digitalcommons.fiu.edu/etd/766.

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Modern electric machine drives, particularly three phase permanent magnet machine drive systems represent an indispensable part of high power density products. Such products include; hybrid electric vehicles, large propulsion systems, and automation products. Reliability and cost of these products are directly related to the reliability and cost of these systems. The compatibility of the electric machine and its drive system for optimal cost and operation has been a large challenge in industrial applications. The main objective of this dissertation is to find a design and control scheme for the best compromise between the reliability and optimality of the electric machine-drive system. The effort presented here is motivated by the need to find new techniques to connect the design and control of electric machines and drive systems. A highly accurate and computationally efficient modeling process was developed to monitor the magnetic, thermal, and electrical aspects of the electric machine in its operational environments. The modeling process was also utilized in the design process in form finite element based optimization process. It was also used in hardware in the loop finite element based optimization process. The modeling process was later employed in the design of a very accurate and highly efficient physics-based customized observers that are required for the fault diagnosis as well the sensorless rotor position estimation. Two test setups with different ratings and topologies were numerically and experimentally tested to verify the effectiveness of the proposed techniques. The modeling process was also employed in the real-time demagnetization control of the machine. Various real-time scenarios were successfully verified. It was shown that this process gives the potential to optimally redefine the assumptions in sizing the permanent magnets of the machine and DC bus voltage of the drive for the worst operating conditions. The mathematical development and stability criteria of the physics-based modeling of the machine, design optimization, and the physics-based fault diagnosis and the physics-based sensorless technique are described in detail. To investigate the performance of the developed design test-bed, software and hardware setups were constructed first. Several topologies of the permanent magnet machine were optimized inside the optimization test-bed. To investigate the performance of the developed sensorless control, a test-bed including a 0.25 (kW) surface mounted permanent magnet synchronous machine example was created. The verification of the proposed technique in a range from medium to very low speed, effectively show the intelligent design capability of the proposed system. Additionally, to investigate the performance of the developed fault diagnosis system, a test-bed including a 0.8 (kW) surface mounted permanent magnet synchronous machine example with trapezoidal back electromotive force was created. The results verify the use of the proposed technique under dynamic eccentricity, DC bus voltage variations, and harmonic loading condition make the system an ideal case for propulsion systems.
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Lin, Ruiyang. "A Design Paradigm for V-shape Interior Permanent-magnet Machines Using Multi-objective Optimization." Thesis, Purdue University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10272940.

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Interior Permanent-magnet Machines (IPMs) have seen wide usage in industry due to their robustness, high efficiency, and low manufacturing cost. Among various IPM topologies, V-shape IPMs have been claimed to exhibit higher power densities. However, designing an IPM has been a challenging task due to the complexity of the rotor structure and magnetic saturation. The objective of this work is to set forth a rigorous design paradigm for V-shape IPMs based on multi-objective optimization. The proposed approach aims to address the multi-disciplinary nature of the design process by incorporating electromagnetic, structural, and thermal analyses. The electromagnetic analysis combines the advantage of an analytical field solution and a magnetic-equivalent-circuit (MEC) approach so it is both computationally efficient and is able to address magnetic nonlinearity in the rotor. The structural analysis uses static stress/strain methods to compute the stress distribution within critical regions in the machine. A thermal analysis based on thermal-equivalent-circuit (TEC) is proposed and the impact of including the thermal analysis on the machine metrics is discussed. Using the proposed approaches, the computational cost is significantly reduced compared to traditional FEA methods. A multi-objective design paradigm incorporating relevant design constraints is set forth. A performance comparison between IPMs and SPMs is conducted for a 2.5-hp motor application.

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Bacco, Giacomo. "Advanced Design and Optimization of Anisotropic Synchronous Machines." Doctoral thesis, Università degli studi di Padova, 2019. http://hdl.handle.net/11577/3423172.

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This work covers many research aspects of anisotropic synchronous motors, which are synchronous reluctance (SyR), permanent magnet assisted synchronous reluctance (PMaSyR) and interior permanent magnet (IPM) machines. In fact, all these kinds of machines exhibit quite a strong reluctance torque component, hence the name anisotropic. From the early 2000s, the design of electric machines started to deeply rely on finite element analysis (FEA) coupled to automatic optimization algorithms. This workflow enabled the machine designer to make fewer initial sizing hypotheses and to explore a wider design space. The drawbacks of this approach are that the time required is long and that the computational resources needed are quite large. However, the computing performances have always been improving over the years, especially when multi-processor architectures became widespread. Therefore nowadays it is common to employ tens or even hundreds of cores on cluster PCs to perform FEA during optimization runs. The thesis is structured as follows. The first part gives the background knowledge needed to develop the topics covered in the following. This comprehends an introduction to the machines studied, some general knowledge about magnetic materials, some basic concepts about the differential evolution (DE) algorithm, and the drawing of fluid rotor flux-barriers. The second part deals with the analytical modeling of SyR and PMaSyR machines. The complete model is nonlinear and may become convoluted to develop especially in an industrial environment. Therefore, using simplifying assumptions, a handful of simple equations can be derived. This simple model is also extended and applied to asymmetric rotor structures, which try to compensate torque harmonics. The third part focuses on applied multi-objective optimizations coupled to FEA for many different case studies. In particular, a SyR motor (SyRM) for pumping applications is optimized, prototyped and tested. Then, a feasibility study on a very low speed PMaSyR motor is carried out through multi-objective optimization. After that, high speed SyRMs are studied and optimized to understand the power limits of this kind of machine. Finally, the DE multi-objective optimization algorithm is also applied to improve the sensorless-control capabilities of anisotropic machines by design.
Questo lavoro analizza molti aspetti di ricerca dei motori sincroni anisotropi, che includono le macchine sincrone a riluttanza pura (SyR), a riluttanza assistita da magneti (PMaSyR) e le macchine a magneti permanenti interni (IPM). Infatti, tutte queste macchine esibiscono una forte componente di riluttanza, da cui il nome anisotrope. Dai primi anni 2000, la progettazione di macchine elettriche ha cominciato a basarsi in modo consistente sull’analisi agli elementi finiti (FEA) accoppiata ad algoritmi di ottimizzazione automatici. Questo flusso di lavoro permette al progettista di fare un minor numero di ipotesi preliminari e di esplorare uno spazio di progetto più ampio. Gli svantaggi di questo approccio sono che il tempo richiesto è lungo e che le risorse computazionali richieste possono essere elevate. Tuttavia, le prestazioni dei computer migliorano di anno in anno, e in particolar modo con la diffusione delle architetture a multi-processore. Pertanto oggigiorno è comune impiegare decine o persino centinaia di core su cluster di PC per effettuare analisi agli elementi finiti durante un’ottimizzazione. La tesi è strutturata nel seguente modo. La prima parte copre le conoscenze di base necessarie a sviluppare gli argomenti trattati nel seguito. C’è quindi un’introduzione alle macchine studiate, delle conoscenze generali sui materiali magnetici e ferromagnetici, alcuni concetti di base sull’algoritmo di ottimizzazione differential evolution (DE) utilizzato, e il disegno delle barriere fluide dei rotori di macchine a riluttanza. Nella seconda parte si sono sviluppati modelli analitici di macchine SyR e PMaSyR. Il modello completo è non lineare e può diventare abbastanza complesso da sviluppare, specialmente in un contesto industriale. Pertanto, usando alcune ipotesi semplificative, si possono derivare alcune semplici equazioni di progetto. Questo modello semplice è anche esteso e applicato a strutture di rotore asimmetriche, che tentano di compensare alcune armoniche di coppia. La terza parte si concentra sull’applicazioni di ottimizzazioni multiobiettivo accoppiate a FEA per alcuni casi di studio. In particolare, si è ottimizzato, prototipato e testato un motore SyRper pompe centrifughe. Poi, è stato condotto uno studio di fattibilità per un motore PMaSyR attraverso ottimizzazioni multi-obiettivo. Dopodiché si sono studiati motori SyRper alte velocità e si sono dedotti i limiti di potenza di questa macchina. Infine l’ottimizzazione DE multi-obiettivo è stata anche applicata per migliorare le capacità di controllo sensorless delle macchine anisotrope già in fase di progetto.
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Kremer, Mickaël. "Electromagnetic design of a disc rotor electric machine as integrated motor-generator for hybrid vehicles." Thesis, Mulhouse, 2016. http://www.theses.fr/2016MULH8792/document.

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Cette thèse présente le dimensionnement d’une machine électrique à rotor disque pour la traction de véhicules hybrides. Un état de l’art complet sur les machines électriques à rotor disque permet de montrer que la machine à flux axial à rotor central est la plus adaptée. Différentes géométries du circuit magnétique sont successivement étudiées et comparées par simulations par éléments finis. Pour maximiser le rendement de la machine, les pertes d’origine électromagnétique sont étudiées. Un modèle analytique des pertes par effet de peau dans les conducteurs de cuivre est proposé et validé par éléments finis. Un second modèle analytique estime les pertes par courant induits dans les aimants permanents pour tous les points de travail de la machine se basant sur uniquement trois simulations par éléments finis permettant ainsi un gain de temps important lors du dimensionnement. Deux méthodes de dimensionnement sont comparées : le dimensionnement manuel par essais/erreurs et l’optimisation multi-objectifs. Cette dernière méthode automatise le dimensionnement et permet une optimisation plus pointue et une forte amélioration des performances. Dans ce cas, la densité de couple a par exemple été augmentée de 29%. La machine à flux axial dimensionnée est comparée avec une machine à flux radial pour véhicules hybrides. Cette comparaison révèle le potentiel de la machine à flux axial avec notamment une densité de couple augmentée de plus de 20%. Enfin, deux prototypes ont été construits et mesurés pour valider les simulations
This PhD presents the design of a disc rotor electric machine for the traction of hybrid vehicles. A complete state of the art enables the selection of the internal rotor axial flux machine which is the most suited to this application. Different geometries of the magnetic circuit are successively studied and compared with finite elements simulations. To maximize the efficiency of the machine losses generated in the magnetic circuit are studied. An analytic model on the skin effect in the copper conductors is proposed and validated with finite elements simulations. A second analytic model estimates the eddy current losses in the permanent magnets for every operating point of the machine based on only three finite element simulations enabling an important time-saving. Two dimensioning methods are compared: the manual dimensioning based on a tries/errors method and the multi-objectives optimization. This last method automates the dimensioning and enables a more refined optimization and a strong improvement of the performances. For example, the torque density has been improved by 29% in that case. The designed axial flux machine is compared to a state of the art radial flux machine for hybrid vehicle. This comparison shows the potential of the axial flux machine with an improvement of the torque density by more than 20%. Finally two prototypes have been built and measured to validate the simulations
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Books on the topic "Electrical machine design and optimization"

1

Lei, Gang, Jianguo Zhu, and Youguang Guo. Multidisciplinary Design Optimization Methods for Electrical Machines and Drive Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49271-0.

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1953-, Villa Tiziano, ed. Synthesis of finite state machines: Logic optimization. Boston: Kluwer Academic, 1997.

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International, Conference on Optimization of Electrical and Electronic Equipment (11th 2000 Brașov Romania). 2008 11th International Conference on Optimization of Electrical and Electronic Equipment: Brasov, Romania, 22-24, May 2008. Piscataway, NJ: IEEE, 2008.

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International, Conference on Optimization of Electrical and Electronic Equipment (11th 2000 Brașov Romania). 2008 11th International Conference on Optimization of Electrical and Electronic Equipment: Brasov, Romania, 22-24, May 2008. Piscataway, NJ: IEEE, 2008.

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International Conference on Optimization of Electrical and Electronic Equipment (11th 2000 Brașov, Romania). 2008 11th International Conference on Optimization of Electrical and Electronic Equipment: Brasov, Romania, 22-24, May 2008. Piscataway, NJ: IEEE, 2008.

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International Conference on Optimization of Electrical and Electronic Equipment (11th 2000 Brașov, Romania). 2008 11th International Conference on Optimization of Electrical and Electronic Equipment: Brasov, Romania, 22-24, May 2008. Piscataway, NJ: IEEE, 2008.

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International Conference on Optimization of Electrical and Electronic Equipment (7th 2000 Brașov, Romania). Proceedings of the 7th International Conference on Optimization of Electrical and Electronic Equipments [sic]: Brașov, May 11-12, 2000. Brașov: Transilvania University Press, 2000.

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Steven, Nowick, ed. Sequential optimization of asynchronous and synchronous finite-state machines: Algorithms and tools. Boston: Kluwer Academic Publishers, 2001.

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Fuhrer, Robert M. Sequential optimization of asynchronous and synchronous finite-state machines: Algorithms and tools. Boston: Kluwer Academic Publishers, 2001.

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Roboam, Xavier, ed. Integrated Design by Optimization of Electrical Energy Systems. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118561812.

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Book chapters on the topic "Electrical machine design and optimization"

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He, Siyuan, Chuan Wang, Xiaowei Yang, Qiao Wang, and Fei Li. "Optimization Design of Mechanical System Human–Machine Interface." In Lecture Notes in Electrical Engineering, 467–74. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-48224-7_55.

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Lei, Gang, Jianguo Zhu, and Youguang Guo. "Design Optimization Methods for Electrical Machines." In Multidisciplinary Design Optimization Methods for Electrical Machines and Drive Systems, 107–59. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49271-0_4.

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Li, Xinyong, and Te Li. "Lightweight Design of Riveting Machine Frame Based on Topology Optimization." In Lecture Notes in Electrical Engineering, 330–38. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6318-2_41.

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Lei, Gang, Jianguo Zhu, and Youguang Guo. "Design Optimization Methods for Electrical Drive Systems." In Multidisciplinary Design Optimization Methods for Electrical Machines and Drive Systems, 161–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49271-0_5.

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Zhu, Zhiying, Linjing Shao, Yuhui Ni, and Bingyu Cong. "Parameter Optimization Design of Axial Permanent Magnet Spherical Magnetic Bearingless Flywheel Machine." In Lecture Notes in Electrical Engineering, 755–64. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1870-4_80.

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Jensen, William R., Thang Q. Pham, and Shanelle N. Foster. "Comparison of Multi-objective Optimization Methods Applied to Electrical Machine Design." In Lecture Notes in Computer Science, 719–30. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12598-1_57.

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Lei, Gang, Jianguo Zhu, and Youguang Guo. "Application-Oriented Design Optimization Methods for Electrical Machines." In Multidisciplinary Design Optimization Methods for Electrical Machines and Drive Systems, 215–35. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49271-0_7.

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Lei, Gang, Jianguo Zhu, and Youguang Guo. "Optimization Methods." In Multidisciplinary Design Optimization Methods for Electrical Machines and Drive Systems, 73–106. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49271-0_3.

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Vita, Valerio, Luca Pugi, Lorenzo Berzi, Francesco Grasso, Raffaele Savi, Massimo Delogu, and Enrico Boni. "Mechatronic Design Optimization of an Electrical Drilling Machine for Trenchless Operations in Urban Environment." In Lecture Notes in Electrical Engineering, 223–28. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66729-0_25.

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Lei, Gang, Jianguo Zhu, and Youguang Guo. "Design Fundamentals of Electrical Machines and Drive Systems." In Multidisciplinary Design Optimization Methods for Electrical Machines and Drive Systems, 25–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49271-0_2.

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Conference papers on the topic "Electrical machine design and optimization"

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Dong, Feng, Er-Ping Li, and Bin-Bin Wang. "Optimization Design of Electrical Resistance Tomography Data Acquisition System." In 2007 International Conference on Machine Learning and Cybernetics. IEEE, 2007. http://dx.doi.org/10.1109/icmlc.2007.4370374.

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Balaji, M., and V. Kamaraj. "Design optimization of Switched Reluctance Machine using Particle Swarm Optimization." In 2011 1st International Conference on Electrical Energy Systems (ICEES). IEEE, 2011. http://dx.doi.org/10.1109/icees.2011.5725322.

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Jiang, Jianan, David Gerada, Zeyuan Xu, Fengyu Zhang, Chris Gerada, and Shoujun Song. "Optimization design of a high temperature machine winding." In 2021 24th International Conference on Electrical Machines and Systems (ICEMS). IEEE, 2021. http://dx.doi.org/10.23919/icems52562.2021.9634241.

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Pompermaier, C., L. Sjoberg, and G. Nord. "Design and optimization of a Permanent Magnet Transverse Flux Machine." In 2012 XXth International Conference on Electrical Machines (ICEM). IEEE, 2012. http://dx.doi.org/10.1109/icelmach.2012.6349932.

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Di Nardo, M., G. Lo Calzo, M. Galea, and C. Gerada. "Structural design optimization of a high speed synchronous reluctance machine." In 2016 XXII International Conference on Electrical Machines (ICEM). IEEE, 2016. http://dx.doi.org/10.1109/icelmach.2016.7732808.

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Liu, Xian, and Wilsun Xu. "A Global Optimization Approach for Electrical Machine Designs." In 2007 IEEE Power Engineering Society General Meeting. IEEE, 2007. http://dx.doi.org/10.1109/pes.2007.385515.

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Cardelli, Ermanno, and Antonio Faba. "Magnetic material modeling for the optimization of the electrical machine design." In 2014 AEIT Annual Conference - From Research to Industry: The Need for a More Effective Technology Transfer (AEIT). IEEE, 2014. http://dx.doi.org/10.1109/aeit.2014.7002038.

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Deihimi, A. "Switched reluctance machine synthesis algorithms based on current PWM control strategy for machine design optimization." In 2008 11th International Conference on Optimization of Electrical and Electronic Equipment (OPTIM). IEEE, 2008. http://dx.doi.org/10.1109/optim.2008.4602386.

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Bacco, Giacomo, Silverio Bolognani, Nicola Bianchi, and Virginia Manzolini. "Self-Sensing-Oriented Optimization of Synchronous Reluctance Machine Design." In 2019 IEEE 10th International Symposium on Sensorless Control for Electrical Drives (SLED). IEEE, 2019. http://dx.doi.org/10.1109/sled.2019.8896320.

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Jin, Hang, Le Zhang, Han-Zhi Ma, Si-Chen Yang, Xiao-Li Yang, and Er-Ping Li. "Machine learning for complex EMI prediction, optimization and localization." In 2017 IEEE Electrical Design of Advanced Packaging and Systems Symposium (EDAPS). IEEE, 2017. http://dx.doi.org/10.1109/edaps.2017.8276967.

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Reports on the topic "Electrical machine design and optimization"

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Resiga, Alin. Design Optimization for a CNC Machine. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.6141.

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Qi, Fei, Zhaohui Xia, Gaoyang Tang, Hang Yang, Yu Song, Guangrui Qian, Xiong An, Chunhuan Lin, and Guangming Shi. A Graph-based Evolutionary Algorithm for Automated Machine Learning. Web of Open Science, December 2020. http://dx.doi.org/10.37686/ser.v1i2.77.

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As an emerging field, Automated Machine Learning (AutoML) aims to reduce or eliminate manual operations that require expertise in machine learning. In this paper, a graph-based architecture is employed to represent flexible combinations of ML models, which provides a large searching space compared to tree-based and stacking-based architectures. Based on this, an evolutionary algorithm is proposed to search for the best architecture, where the mutation and heredity operators are the key for architecture evolution. With Bayesian hyper-parameter optimization, the proposed approach can automate the workflow of machine learning. On the PMLB dataset, the proposed approach shows the state-of-the-art performance compared with TPOT, Autostacker, and auto-sklearn. Some of the optimized models are with complex structures which are difficult to obtain in manual design.
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