Analysis of AC link topologies in non-isolated DC/DC triple active bridge converter for current stress minimization

This paper presents analysis of the non-isolated DC/DC triple active bridge (TAB) converter under various purely inductor-based AC link topologies. The objective of the analysis is to find the topology that incorporates the least value of the AC link inductors which leads to reduced converter footprint in addition to minimum internal current stresses. Modelling of the TAB under each of the different topologies is presented in per unit expressions of power transfer and reactive power assuming fundamental harmonic analysis. The power expressions are used to calculate the inductor values necessary to achieve same rated power transfer of Dual Active Bridge (DAB) converter for the sake of standardizing comparison. On this basis, the topology requiring the least value of interface inductors, hence lowest footprint, is identified. Furthermore, based on phase shift control, particle swarm optimization (PSO) is used to calculate optimal phase shift ratios in each of the proposed topologies to minimize reactive power loss (hence current stress). The topology with minimum stresses is therefore identified and the results are substantiated using a Matlab-Simulink model to verify the theoretical analysis

Generic closed loop controller for power regulation in dual active bridge DC-DC converter with current stress minimization

This paper presents a comprehensive and generalized analysis of the bidirectional dual active bridge (DAB) DC/DC converter using triple phase shift (TPS) control to enable closed loop power regulation while minimizing current stress. The key new achievements are: a generic analysis in terms of possible conversion ratios/converter voltage gains (i.e. Buck/Boost/Unity), per unit based equations regardless of DAB ratings, and a new simple closed loop controller implementable in real time to meet desired power transfer regulation at minimum current stress. Per unit based analytical expressions are derived for converter AC RMS current as well as power transferred. An offline particle swarm optimization (PSO) method is used to obtain an extensive set of TPS ratios for minimizing the RMS current in the entire bidirectional power range of - 1 to 1 per unit. The extensive set of results achieved from PSO presents a generic data pool which is carefully analyzed to derive simple useful relations. Such relations enabled a generic closed loop controller design that can be implemented in real time avoiding the extensive computational capacity that iterative optimization techniques require. A detailed Simulink DAB switching model is used to validate precision of the proposed closed loop controller under various operating conditions. An experimental prototype also substantiates the results achieved

Generalized small-signal modelling of dual active bridge DC/DC converter

this paper presents a novel generalised approach of the small-signal modelling of dual active bridge (DAB) DC/DC converter. The adopted analysis is based on a per-unit fundamental frequency representation of the DAB. The outcome of the proposed modelling approach is a small signal, linearised, state-space DAB model; which is considered as a main building block for future control applications. The developed small signal DAB model includes all possible degrees of freedom affecting the performance of the DAB; this includes the voltage conversion ratio to allow the study of all DAB operation modes (i.e.: unity-gain and buck/boost modes.). Furthermore, since triple phase shift control (TPS) is used in this development work, the proposed model incorporates phase shift in addition to duty ratios. This feature allows for bridge voltage regulation, which is essential for efficient DAB operation in the case of buck/boost operation. Another key achievement is that the proposed small signal modelling methodology can be applied to any bidirectional DC-DC converter regardless of ratings, parameter values and number of ports. Extensive simulation is carried out to verify the proposed analysis

Sjögren Syndrome Complicated by Mucosa-Associated Lymphoid Tissue Lymphoma and Lymphocytic Interstitial Pneumonia.

Sjögren syndrome (SS) is an autoimmune disease with exocrine glands dysfunction and multiorgan involvement. It is associated with increased risk of lymphoproliferative disorders, especially B-cell marginal zone lymphoma. While the role of F-18 Fluorodeoxyglucose position emission tomography/computed tomography (F-18 FDG PET/CT) for evaluation of lymphoma has been established, its use in patients with a chronic history of SS to evaluate for possible lymphoproliferative disorders or multiorgan involvement is limited. We present a case of chronic SS in which F-18 FDG PET/CT demonstrated FDG avid intraparotid and cervical lymph nodes pathologically proven to be mucosa-associated lymphoid tissue lymphoma. In addition, the patient had bibasilar cystic changes consistent with lymphocytic interstitial pneumonia

Macroeconomic Variables, Government Effectiveness and Sovereign Credit Rating: A Case of Egypt

Sovereign credit rating reflects the country ability to meet its financial obligations (at present and in future) on its maturities, therefore, it is an important indicator that concerns international financial institutions and foreign investors who are interested in foreign direct investment in order to know the minimum expectation of risks that can be faced in specific country. This paper aims to i) examine the effect of macroeconomic variables on the Egyptian sovereign credit rating (SCR) and ii) also investigate the impact of investment environment (measured by government effectiveness) on the SCR using the dynamic ordinary least squares (DOLS) method over the period from 1990 to 2014.  The results indicate that GDP growth, inflation, fiscal balance, reserves, current account balance, public domestic debt, and the government effectiveness have a significant impact on the sovereign credit rating in Egypt. This study has important implications for investors and policymakers

Thymoquinone and curcumin attenuate gentamicin-induced renal oxidative stress, inflammation and apoptosis in rats

The present study was aimed to investigate the possible protective effects of thymoquinone (TQ) and curcumin (Cur) on gentamicin (GM)-induced nephrotoxicity in rats. Rats were divided into four groups as follows: group 1 received normal saline and served as normal controls, group 2 received GM only, group 3 concurrently received GM and TQ and group 4 concurrently received GM and Cur. At day 21, rats were sacrificed and samples were collected for assaying serum tumor necrosis factor alpha (TNF-α), urea and creatinine levels, and renal lipid peroxidation, glutathione (GSH) content as well as glutathione peroxidase (GPx) and superoxide dismutase (SOD) activities. In addition, kidneys were collected for histopathological examination and immunohistochemical determination of the antiapoptotic protein, B-cell lymphoma 2 (Bcl-2). The biochemical results showed that GM-induced nephrotoxicity was associated with a significant increase in serum TNF-α, urea and creatinine as well as renal lipid peroxidation. On the other hand, renal GSH content and GPx and SOD activities were significantly declined. Concomitant administration of either TQ or Cur efficiently alleviated the altered biochemical and histopathological features. In conclusion, both TQ and Cur showed more or less similar marked renoprotective effect against GM-induced nephrotoxicity through their antioxidant, anti-inflammatory and anti-apoptotic efficacies

Applying Bootstrap Robust Regression Method on Data with Outliers

Identification and assessment of outliers have a key role in Ordinary Least Squares (OLS) regression analysis. This paper presents a robust two-stage procedure to identify outlying observations in regression analysis. The exploratory stage identifies leverage points and vertical outliers through a robust distance estimator based on Minimum Covariance Determinant (MCD). After deletion of these points, the confirmatory stage carries out an OLS analysis on the remaining subset of data and investigates the effect of adding back in the previously deleted observations. Cut-off points pertinent to different diagnostics are generated by bootstrapping and the cases are definitely labeled as good-leverage, bad leverage, vertical outliers and typical cases. This procedure is applied to four examples taken from the literature and it is effective in rightly pinpointing outlying observations, even in the presence of substantial masking. This procedure is able to identify and correctly classify vertical outliers, good and bad leverage points, through the use of jackknife-after-bootstrap robust cut-off points. Moreover its two stage structure makes it interactive and this enables the user to reach a deeper understanding of the dataset main features than resorting to an automatic procedure