949 resultados para brushless machines


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High temperature superconducting (HTS) synchronous motors can offer significant weight and size reductions, as well as improved efficiency, over conventional copper-wound machines due to the higher current density of high temperature superconducting (HTS) materials. In order to optimise the design parameters and performance of such a machine, this paper proposes a basic physical model of an air-cored HTS synchronous motor with a copper armature winding and HTS field winding. An analytical method for the field analysis in the synchronous motor is then presented, followed by a numerical finite element analysis (FEA) model to verify the analytical solution. The model is utilised to study the influence of the geometry of the HTS coils on the magnetic field at the armature winding, and geometrical parameter optimisation is carried out using this theoretical model to obtain a more sinusoidal magnetic field at the armature, which has a major influence on the performance of the motor.

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Operation of induction machines in the high-speed and/or high-torque range requires field-weakening to comply with voltage and current physical limitations. This paper presents an anti-windup approach to this problem: rather than developing an ad-hoc field weakening strategy in the high-speed region, we equip an unconstrained vector-control design with an anti-windup module that automatically adjusts the current and flux set-points so that voltage and current constraints are satisfied at every operating point. The anti-windup module includes a feedforward modification of the set point aimed at maximizing the available torque in steady-state and a feedback modification of the controller based on an internal model-based antiwindup scheme. This paper includes a complete stability analysis of the proposed solution and presents encouraging experimental results on an industrial drive. © 2012 IEEE.

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Pancake or racetrack coils wound with second generation high-temperature superconductors (2G HTSs) are important elements for numerous applications of HTS. The applications of these coils are primarily in rotating machines such as motors and generators where they must withstand external magnetic fields from various orientations. The characterization of 2G HTS coils is mostly focused on AC loss assessment, critical current and maximum magnetic field evaluation. In this study, racetrack coils will be placed in different orientations of external magnetic fields - Jc (Ic) versus angle measurements will be performed and interpreted. Full attention is paid to studies of anisotropy Jc versus angle curves for short samples of 2G HTS tapes. As will be shown, the shape of the Jc versus angle curves for tapes has a strong influence on the Jc (Ic) versus angle curves for coils. In this work, a unique and unpredicted behavior of the Jc versus angle curves for the 2G HTS racetrack coils was found. This will be analyzed and fully explained. © 2013 IOP Publishing Ltd.

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We introduce a conceptually novel structured prediction model, GPstruct, which is kernelized, non-parametric and Bayesian, by design. We motivate the model with respect to existing approaches, among others, conditional random fields (CRFs), maximum margin Markov networks (M3N), and structured support vector machines (SVMstruct), which embody only a subset of its properties. We present an inference procedure based on Markov Chain Monte Carlo. The framework can be instantiated for a wide range of structured objects such as linear chains, trees, grids, and other general graphs. As a proof of concept, the model is benchmarked on several natural language processing tasks and a video gesture segmentation task involving a linear chain structure. We show prediction accuracies for GPstruct which are comparable to or exceeding those of CRFs and SVMstruct.

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A sensorless scheme is presented for a two-phase permanent-magnet linear machine targeted for use in marine wave-power generation. This is a field where system reliability is a key concern. The scheme is able to extract the effective inductance and back-emf of the machine's phases simultaneously from measurements of the current ripple present on the power electronic converter. These measurements can then be used to estimate position. An enhancement to the scheme in the presence of spatially-varying mutual inductance between phases allows more accurate and reliable tracking from indutance-based measurements than would otherwise be expected. This scheme is able to operate at any speed including, critically, when stationary. Experimental results show promise for the scheme, although some work to reduce the level of noise would be desirable. © 2013 IEEE.

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In this paper, the authors investigate a number of design and market considerations for an axial flux superconducting electric machine design that uses high temperature superconductors. The axial flux machine design is assumed to utilise high temperature superconductors in both wire (stator winding) and bulk (rotor field) forms, to operate over a temperature range of 65-77 K, and to have a power output in the range from 10s of kW up to 1 MW (typical for axial flux machines), with approximately 2-3 T as the peak trapped field in the bulk superconductors. The authors firstly investigate the applicability of this type of machine as a generator in small- and medium-sized wind turbines, including the current and forecasted market and pricing for conventional turbines. Next, a study is also carried out on the machine's applicability as an in-wheel hub motor for electric vehicles. Some recommendations for future applications are made based on the outcome of these two studies. Finally, the cost of YBCO-based superconducting (2G HTS) wire is analysed with respect to competing wire technologies and compared with current conventional material costs and current wire costs for both 1G and 2G HTS are still too great to be economically feasible for such superconducting devices.

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The notch and strain rate sensitivity of non-crimp glass fibre/vinyl-ester laminates subjected to uniaxial tensile loads has been investigated experimentally. Two sets of notch configurations were tested; one where circular holes were drilled and another where fragment simulating projectiles were fired through the plate creating a notch. Experiments were conducted for strain rates ranging from 10-4 s-1 to 102 s-1 using servo hydraulic machines. A significant increase in strength with increasing strain rate was observed for both notched and un-notched specimens. High speed photography revealed changes in failure mode, for certain laminate configurations, as the strain rate increased. The tested laminate configurations showed fairly small notch sensitivity for the whole range of strain rates. © 2008 Elsevier Ltd. All rights reserved.

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The notch and strain rate sensitivity of non-crimp glass fibre/vinyl-ester laminates subjected to uniaxial tensile loads has been investigated experimentally. Two set of notch configurations were tested; one where circular holes were drilled and another where fragment simulating projectiles were fired through the plate creating a notch. Experiments were conducted for strain rates ranging from 10-4/s to 102/s using servo hydraulic machines. A significant increase in strength with increasing strain rate was observed for both notched and unnotched specimens. High speed photography revealed changes in failure mode, for certain laminate configurations, as the strain rate increased. The tested laminate configurations showed fairly small notch sensitivity for the whole range of strain rates.

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We present Random Partition Kernels, a new class of kernels derived by demonstrating a natural connection between random partitions of objects and kernels between those objects. We show how the construction can be used to create kernels from methods that would not normally be viewed as random partitions, such as Random Forest. To demonstrate the potential of this method, we propose two new kernels, the Random Forest Kernel and the Fast Cluster Kernel, and show that these kernels consistently outperform standard kernels on problems involving real-world datasets. Finally, we show how the form of these kernels lend themselves to a natural approximation that is appropriate for certain big data problems, allowing $O(N)$ inference in methods such as Gaussian Processes, Support Vector Machines and Kernel PCA.

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Toward our comprehensive understanding of legged locomotion in animals and machines, the compass gait model has been intensively studied for a systematic investigation of complex biped locomotion dynamics. While most of the previous studies focused only on the locomotion on flat surfaces, in this article, we tackle with the problem of bipedal locomotion in rough terrains by using a minimalistic control architecture for the compass gait walking model. This controller utilizes an open-loop sinusoidal oscillation of hip motor, which induces basic walking stability without sensory feedback. A set of simulation analyses show that the underlying mechanism lies in the "phase locking" mechanism that compensates phase delays between mechanical dynamics and the open-loop motor oscillation resulting in a relatively large basin of attraction in dynamic bipedal walking. By exploiting this mechanism, we also explain how the basin of attraction can be controlled by manipulating the parameters of oscillator not only on a flat terrain but also in various inclined slopes. Based on the simulation analysis, the proposed controller is implemented in a real-world robotic platform to confirm the plausibility of the approach. In addition, by using these basic principles of self-stability and gait variability, we demonstrate how the proposed controller can be extended with a simple sensory feedback such that the robot is able to control gait patterns autonomously for traversing a rough terrain. © 2010 Springer Science+Business Media, LLC.

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Robotics researchers increasingly agree that ideas from biology and self-organization can strongly benefit the design of autonomous robots. Biological organisms have evolved to perform and survive in a world characterized by rapid changes, high uncertainty, indefinite richness, and limited availability of information. Industrial robots, in contrast, operate in highly controlled environments with no or very little uncertainty. Although many challenges remain, concepts from biologically inspired (bio-inspired) robotics will eventually enable researchers to engineer machines for the real world that possess at least some of the desirable properties of biological organisms, such as adaptivity, robustness, versatility, and agility.

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This article presents a framework that describes formally the underlying unsteady and conjugate heat transfer processes that are undergone in thermodynamic systems, along with results from its application to the characterization of thermodynamic losses due to irreversible heat transfer during reciprocating compression and expansion processes in a gas spring. Specifically, a heat transfer model is proposed that solves the one-dimensional unsteady heat conduction equation in the solid simultaneously with the first law in the gas phase, with an imposed heat transfer coefficient taken from suitable experiments in gas springs. Even at low volumetric compression ratios (of 2.5), notable effects of unsteady heat transfer to the solid walls are revealed, with thermally induced thermodynamic cycle (work) losses of up to 14% (relative to the work input/output in equivalent adiabatic and reversible compression/expansion processes) at intermediate Péclet numbers (i.e., normalized frequencies) when unfavorable solid and gas materials are selected, and closer to 10-12% for more common material choices. The contribution of the solid toward these values, through the conjugate variations attributed to the thickness of the cylinder wall, is about 8% and 2% points, respectively, showing a maximum at intermediate thicknesses. At higher compression ratios (of 6) a 19% worst-case loss is reported for common materials. These results suggest strongly that in designing high-efficiency reciprocating machines the full conjugate and unsteady problem must be considered and that the role of the solid in determining performance cannot, in general, be neglected. © 2014 Richard Mathie, Christos N. Markides, and Alexander J. White. Published with License by Taylor & Francis.

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The ability to generate a permanent, stable magnetic field unsupported by an electromotive force is fundamental to a variety of engineering applications. Bulk high temperature superconducting (HTS) materials can trap magnetic fields of magnitude over ten times higher than the maximum field produced by conventional magnets, which is limited practically to rather less than 2 T. In this paper, two large c-axis oriented, single-grain YBCO and GdBCO bulk superconductors are magnetized by the pulsed field magnetization (PFM) technique at temperatures of 40 and 65 K and the characteristics of the resulting trapped field profile are investigated with a view of magnetizing such samples as trapped field magnets (TFMs) in situ inside a trapped flux-type superconducting electric machine. A comparison is made between the temperatures at which the pulsed magnetic field is applied and the results have strong implications for the optimum operating temperature for TFMs in trapped flux-type superconducting electric machines. The effects of inhomogeneities, which occur during the growth process of single-grain bulk superconductors, on the trapped field and maximum temperature rise in the sample are modelled numerically using a 3D finite-element model based on the H-formulation and implemented in Comsol Multiphysics 4.3a. The results agree qualitatively with the observed experimental results, in that inhomogeneities act to distort the trapped field profile and reduce the magnitude of the trapped field due to localized heating within the sample and preferential movement and pinning of flux lines around the growth section regions (GSRs) and growth sector boundaries (GSBs), respectively. The modelling framework will allow further investigation of various inhomogeneities that arise during the processing of (RE)BCO bulk superconductors, including inhomogeneous Jc distributions and the presence of current-limiting grain boundaries and cracks, and it can be used to assist optimization of processing and PFM techniques for practical bulk superconductor applications. © 2014 IOP Publishing Ltd.

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Mobility of wheeled or legged machines can be significantly increased if they are able to move from a solid surface into a three-dimensional space. Although that may be achieved by addition of flying mechanisms, the payload fraction will be the limiting factor in such hybrid mobile machines for many applications. Inspired by spiders producing draglines to assist locomotion, the paper proposes an alternative mobile technology where a robot achieves locomotion from a solid surface into a free space. The technology resembles the dragline production pathway in spiders to a technically feasible degree and enables robots to move with thermoplastic spinning of draglines. As an implementation, a mobile robot has been prototyped with thermoplastic adhesives as source material of the draglines. Experimental results show that a dragline diameter range of 1.17-5.27 mm was achievable by the 185 g mobile robot in descending locomotion from the solid surface of a hanging structure with a power consumption of 4.8 W and an average speed of 5.13 cm min(-1). With an open-loop controller consisting of sequences of discrete events, the robot has demonstrated repeatable dragline formation with a relative deviation within -4% and a length close to the metre scale.

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THERE ARE MANY different kinds of robots: factory automation systems that weld and assemble car engines; machines that place chocolates into boxes; medical devices that support surgeons in operations requiring high-precision manipulation; cars that drive automatically over long distances; vehicles for planetary exploration; mechanisms for powerline or oil platform inspection; toys and educational toolkits for schools and universities; service robots that deliver meals, clean floors, or mow lawns; and "companion robots" that are real partners for humans and share our daily lives. In a sense, all these robots are inspired by biological systems; it's just a matter of degree. A driverless vehicle imitates animals moving autonomously in the world.© 2012 ACM.