For RRAM to be a cost-competitive candidate for high-density and high-capacity commercial products, some architectural-level challenges must be tackled. In this paper, research results that advance the design of high-...
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For RRAM to be a cost-competitive candidate for high-density and high-capacity commercial products, some architectural-level challenges must be tackled. In this paper, research results that advance the design of high-density RRAM arrays are presented. We first focus on the scaling effects of on-chip interconnects on RRAM array performance. Due to the continuously shrinking process feature size, the voltage drop along the interconnect gradually reduces the voltage available to operate the RRAM device. To more efficiently analyze this effect for an arbitrary array size, a compact array model is developed. Simulations using this model determine the maximum achievable array size for future technology nodes. A compact, one-transistor-N-RRAM (1TNR) array architecture, with corresponding read/write and decoding schemes, that achieves high RRAM density is then introduced. A proof-of-concept 1T4R test chip with fully integrated RRAM devices is described. For this test chip, a particular sequence to form the cross-point RRAM array is presented. Measurement results of successful array operations demonstrate the feasibility and reliability of the proposed high-density architecture.
Large photovoltaic arrays are becoming common as the world moves to replace fossil-fuelled electricity generators. As the array size and project cost increase, it becomes increasingly important to know accurately what...
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Large photovoltaic arrays are becoming common as the world moves to replace fossil-fuelled electricity generators. As the array size and project cost increase, it becomes increasingly important to know accurately what the array's performance will be before it is built. Large arrays inevitably contain modules with a spread of performance characteristics such as short-circuit current and open-circuit voltage, and suffer from temperature differences between modules. In this first study of these problems, a model has been developed that accurately predicts the behaviour of a photovoltaic array subject to variability between modules and inhomogeneity of cell temperature across the array. The model was applied to a real rooftop array consisting of 912 modules (298 kW nominal peak power). Based on measured string currents, the predicted average string temperature was compared the temperature measured by a radiometric survey using a drone-mounted IR camera and matched very well. The five-parameter model of cell characteristics was fitted to manufacturer's data, with highest weighting given to the region around the maximum-power point (MPP) where a real array should operate via active MPP tracking. The model was used to explore separately the effects of a spread in module characteristics arising in the manufacturing process and of temperature inhomogeneity across the array. The current in each module of a string was constrained to be the same, and the voltage of every parallel-connected string was also constrained to be the same. These constraints lead to greater power loss than is predicted based on an average module at an average temperature. Compared to a hypothetical array assembled from identical average modules at the same average temperature, variability caused a loss of power of about 2%, depending on the detailed form of the distribution function chosen to represent the spread of characteristics in the manufacturer's tolerance band. As a rule of thumb, de-rating the
Wave energy converters absorb wave power by mechanical damping for conversion into electricity and multi-float systems may have high capture widths. The kinetic energy of the floats causes waves to be radiated, genera...
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Wave energy converters absorb wave power by mechanical damping for conversion into electricity and multi-float systems may have high capture widths. The kinetic energy of the floats causes waves to be radiated, generating radiation damping. The total wave power absorbed is thus due to mechanical and radiation damping. A floating offshore wind turbine platform also responds dynamically and damping plates are generally employed on semi-submersible configurations to reduce motion, generating substantial drag which absorbs additional wave power. Total wave power absorption is analysed here by linear wave diffraction-radiation-drag models for a multi-float wave energy converter and an idealised wind turbine platform, with response and mechanical power in the wave energy case compared with wave basin experiments, including some directional spread wave cases, and accelerations compared in the wind platform case. The total power absorption defined by capture width is input into a far field array model with directional wave spreading. Wave power transmission due a typical wind turbine array is only reduced slightly (less than 5% for a 10 x 10 platform array) but may be reduced significantly by rows of wave energy converters (by up to about 50%).
In this contribution we analyze the integrity of the GNSS array model through the socalled uniformly most powerful invariant (UMPI) test-statistics and their corresponding minimal detectable biases (MDBs). The model c...
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ISBN:
(纸本)9783319305301;9783319245485
In this contribution we analyze the integrity of the GNSS array model through the socalled uniformly most powerful invariant (UMPI) test-statistics and their corresponding minimal detectable biases (MDBs). The model considered is characterized by multiple receivers/ satellites with known coordinates where the multi-frequency carrier-phase and pseudo-range observables are subject to atmospheric (ionospheric and tropospheric) delays, receiver and satellite clock biases, as well as instrumental delays. Highlighting the role played by the model's misclosures, analytical multivariate expressions of a few leading teststatistics together with their MDBs are studied that are further accompanied by numerical results of the three GNSSs GPS, Galileo and BeiDou.
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