Switching frequency reduction in pulse-width modulated multilever converters and systems

Multilevel converters have attracted a great deal of interest in recent years since they offer a number of advantages in many high voltage and high power applications, such as adjustable speed electric motor drives and power systems through Flexible Alternating Current Transmission Systems (FACTS) controllers and active harmonic filters. They can reach high voltages with low harmonics without the use of transformers or series-connected synchronised switching devices by their unique structures. Along with proper Pulse-Width Modulation (PWM) control scheme, they can also provide lower cost, higher performance, lower Electro-Magnetic Interference (EMI), and higher efficiency than the traditional PWM converters. However, switching losses become a serious issue in high power applications. In order to improve the efficiency and reliability of the system, and reduce the size of the output filter, the stresses on the semiconductors and the development and manufacturing costs, reducing the switching frequency and associated losses of multilevel PWM converters and systems needs to be properly addressed. The thesis gives an overview on multilevel converter topologies and control schemes. It then presents mathematical analysis towards further understanding of the Neutral-Point-Clamped (NPC) and the Flying Capacitor (FC) converters. The Fundamental Frequency Sinusoidal PWM (FF-SPWM) control method is examined as a potential "carrier" based approach in reducing the converter switching frequency and associated losses. The performance of multi-modular parallel connected systems based on the NPC and FC converters as a building block is reported along with the influence of the multicarrier PWM techniques. The voltage-unbalancing problem of the FC converter is addressed and a solution is provided. DSP based controllers for the three-level and the five-level FC converters have been developed and experimentally verified. Results taken from the laboratory prototype are presented to support the theoretical part of the project

Palm Print Edge Extraction Using Fractional Differential Algorithm

Algorithm based on fractional difference was used for the edge extraction of thenar palm print image. Based on fractional order difference function which was deduced from classical fractional differential G-L definition, three filter templates were constructed to extract thenar palm print edge. The experiment results showed that this algorithm can reduce noise and detect rich edge details and has higher SNR than traditional methods

A novel safety assurance method based on the compound equivalent modeling and iterate reduce particle‐adaptive Kalman filtering for the unmanned aerial vehicle lithium ion batteries.

The safety assurance is very important for the unmanned aerial vehicle lithium ion batteries, in which the state of charge estimation is the basis of its energy management and safety protection. A new equivalent modeling method is proposed for the mathematical expression of different structural characteristics, and an improved reduce particle-adaptive Kalman filtering model is designed and built, in which the incorporate multiple featured information is absorbed to explore the optimal representation by abandoning the redundant and abnormal information. And then, the multiple parameter identification is investigated that has the ability of adapting the current varying conditions, according to which the hybrid pulse power characterization test is accommodated. As can be known from the experimental results, the polynomial fitting treatment is carried out by conducting the curve fitting treatment and the maximum estimation error of the closed-circuit-voltage is 0.48% and its state of charge estimation error is lower than 0.30% in the hybrid pulse power characterization test, which is also within 2.00% under complex current varying working conditions. The iterate calculation process is conducted for the unmanned aerial vehicle lithium ion batteries together with the compound equivalent modeling, realizing its adaptive power state estimation and safety protection effectively

Co-estimation of state-of-charge and state-of-health for high-capacity lithium-ion batteries.

To address the challenges of efficient state monitoring of lithium-ion batteries in electric vehicles, a co-estimation algorithm of state-of-charge (SOC) and state-of-health (SOH) is developed. The algorithm integrates techniques of adaptive recursive least squares and dual adaptive extended Kalman filtering to enhance robustness, mitigate data saturation, and reduce the impact of colored noise. At 25C, the algorithm is tested and verified under dynamic stress test (DST) and Beijing bus DST conditions. Under the Beijing bus DST condition, the algorithm achieves a mean absolute error (MAE) of 0.17% and a root mean square error (RMSE) of 0.19% for SOC estimation, with a convergence time of 4 s. Under the DST condition, the corresponding values are 0.05% for MAE, 0.07% for RMSE, and 5 s for convergence time. Moreover, in this research, the SOH is described as having internal resistance. Under the Beijing bus DST condition, the MAE and the RMSE of the estimated internal resistance of the proposed approach are 0.018% and 0.075%, with the corresponding values of 0.014% and 0.043% under the DST condition. The results of the experiments provide empirical evidence for the challenges associated with the efficacious estimation of SOC and SOH

Photocatalytic degradation of AZO dyes by supported TiO2+UV in aqueous solution

The photocatalytic degradation performance of photocatalysts TiO2 supported on 13-X, Na-Y, 4A zeolites with different loading content was evaluated using the photocatalytic oxidation of dyes direct fast scarlet 4BS and acid red 3B in aqueous medium. The results showed that the best reaction dosage of TiO2-zeolite catalysts is about 2 g/l and the photocatalytic kinetics follows first order for all supported catalysts. The photocatalytic activity order of the three series catalysts is 13X type >Y type >4A type. The physical state of titanium dioxide on the supports is evaluated by X-ray photoelectron spectra (XPS), powder X-ray diffraction (XRD), BET, and FTIR. (C) 2000 Elsevier Science Ltd. All rights reserved

Clustered Distribution of Natural Product Leads of Drugs in the Chemical Space as Influenced by the Privileged Target-Sites

10.1038/srep09325Scientific Reports

Resilience of infaunal ecosystems during the Early Triassic greenhouse Earth

The Permian-Triassic mass extinction severely depleted biodiversity, primarily observed in the body fossil of well-skeletonized animals. Understanding how whole ecosystems were affected and rebuilt following the crisis requires evidence from both skeletonized and soft-bodied animals; the best comprehensive information on soft-bodied animals comes from ichnofossils. We analyzed abundant trace fossils from 26 sections across the Permian-Triassic boundary in China and report key metrics of ichnodiversity, ichnodisparity, ecospace utilization, and ecosystem engineering. We find that infaunal ecologic structure was well established in the early Smithian. Decoupling of diversity between deposit feeders and suspension feeders in carbonate ramp-platform settings implies that an effect of trophic group amensalism could have delayed the recovery of nonmotile, suspension-feeding epifauna in the Early Triassic. This differential reaction of infaunal ecosystems to variable environmental controls thus played a substantial but heretofore little appreciated evolutionary and ecologic role in the overall recovery in the hot Early Triassic ocean

ESC-Derived Basal Forebrain Cholinergic Neurons Ameliorate the Cognitive Symptoms Associated with Alzheimer’s Disease in Mouse Models

SummaryDegeneration of basal forebrain cholinergic neurons (BFCNs) is associated with cognitive impairments of Alzheimer’s disease (AD), implying that BFCNs hold potentials in exploring stem cell-based replacement therapy for AD. However, studies on derivation of BFCNs from embryonic stem cells (ESCs) are limited, and the application of ESC-derived BFCNs remains to be determined. Here, we report on differentiation approaches for directing both mouse and human ESCs into mature BFCNs. These ESC-derived BFCNs exhibit features similar to those of their in vivo counterparts and acquire appropriate functional properties. After transplantation into the basal forebrain of AD model mice, ESC-derived BFCN progenitors predominantly differentiate into mature cholinergic neurons that functionally integrate into the endogenous basal forebrain cholinergic projection system. The AD mice grafted with mouse or human BFCNs exhibit improvements in learning and memory performances. Our findings suggest a promising perspective of ESC-derived BFCNs in the development of stem cell-based therapies for treatment of AD