A high performance PWM inverter voltage-fed induction machines drive with an alternative strategy for speed control

In this paper, the method of behaviour model control is applied to an induction motor with its mechanical load in order to increase the robustness of the vector control and to keep its performances despite the presence of perturbations (parameters variations, abrupt load variations, etc). The idea of the proposed control is interesting and useful. It induces adding supplementary control inputs, which yield the process to follow the model. The distinguished feature of this control design is that it achieves the same performances as the Field Oriented Control without the need for heavy and expensive gain tuning. The proposed strategy minimizes the energy used for the control and ensures the stabilization and excellent tracking performance of the system. Simplicity of the method, minimization of the required energy and the elimination of the need for gain tuning are the main positive features of the proposed approach

Vektorsko upravljanje dvostruko pobuđenim sinkronim strojem kao integriranim starterom-alternatorom

The paper proposes a double excited synchronous machine as integrated starter--alternator for future automobiles applications. Particularly, the biaxial excitation synchronous machine (BESM) is proposed for its high efficiency and wide constant power speed range. As the integrated starter--alternator system combines both starter and generator functions in a single electric machine, an alternative vector control strategy for BESM is developed and detailed to allow operation in the two modes at unity power factor operation by setting d-axis current to be zero and q-axis current to be constant and equal to its value that cancel the q-axis flux. In such conditions, the BESM torque can be controlled by the dc-excitation current and the required dc-bus voltage can be regulated within the 42V PowerNet specifications. To overcome the slowness dc-excitation current response, which is due to higher dc-field excitation time constant, and to increase the torque response quickness, the control of the magnetising current is proposed instead of the d-axis current. Implementation and simulation results validate the proposed scheme and provide a practical solution for an integrated starter-alternator.U radu je predložena upotreba dvostruko pobuđenog sinkronog stroja kao integriranog startera-alternatora, za buduće primjene u automobilskoj industriji. Preciznije, predložena je upotreba biaksijalno pobuđenog sinkronog stroja (BESM) zbog visoke korisnosti i širokog raspona područja konstantne snage. Kao integrirani starter-alternator, sustav kombinira funkcije i startera i generatora u jednom električnom stroju. Razvijen je i detaljno opisan alternativni pristup vektorskom upravljanju BESM-om za omogućavanje rada u dva moda uz jedinični faktor snage postavljanjem d-osi struje u nulu i q-osi struje na konstantnu vrijednost koja poništava tok u q-osi. U ovakvim uvjetima, BESM momentom moguće je upravljati istosmjernom uzbudnom strujom i traženi napon dc-sabirnice moguće je regulirati unutar 42V PowerNet specifikacija. Za prevladavanje sporog odziva na istosmjernu uzbudnu struju koji nastaje zbog veće vremenske konstante magnetskog polja uzbude, a s ciljem ubrzanja odziva momenta, predloženo je upravljanje strujom magnetizacije umjesto strujom u d-osi. Implementacijski i simulacijski rezultati potvrđuju predloženi pristup i pružaju praktično rješenje za integrirani starter-alternator

State of charge estimation based on adaptive algorithm for Lead-Acid battery

The usage of batteries in recent years has become widespread in many fields e.g. in electric vehicles, energy renewable and stand-alone systems which require a robust approach for estimation of the state of charge (SOC). The SOC represents an important factor to guaranty safe operations. A lot of methods have been used to predict the state of charge. The coulomb counting method is the famous and widely used among them, but have limitation due to its accuracy. Another used approach is the Kalman Filter, which improves the estimation efficiency, to reach a good performance in SOC prediction. The version of adaptive extended Kalman filter (AEKF) technique is applied in this paper. This paper presents an experimental performance of technique of Kalman filter, for solving the problem of accurate SOC. The method is used to compute the terminal voltage in such a way to estimate the SOC. The proposed algorithm is based on preselected Thevenin model after the identification of its parameters. It has been used to predict the SOC based on nonlinear equations, and evaluation of the approach is verified with the experimental results. The final results signify that the estimation matched with the proposed model and the algorithm is performed optimally, thus the maximum soc estimation error is the fines

Distributed Photovoltaic Architecture for HVDC-bus Feeding with a Simple Evaluation of Optimal Tracking

International audienceThis contribution describes, compares, and analyses two structures and their operating modes dedicated to renewable energy production from photovoltaic (PV) sources. Between the two different technical approaches, photovoltaic sources placed in a distributed architecture supplying a high DC voltage HVDC bus points large advantages. Thus, after preliminary comparison of both solutions and concluding phases, this efficient solution finally constitutes the main original analysis presented in this contribution. The distributed PV structure is investigated, implemented and simulated in an original way under the OrCAD/Pspice software environment. The adaptation stage for maximum power transfer is modelled in detail. A method to calculate the optimal duty cycle for optimal use of PV panels power is proposed, tested and validated by the use of a marketed PV module datasheet

Modeli umjetne neuronske mreže za predviđanje gustoće i kinematičke viskoznosti različitih sustava biogoriva i njihovih mješavina s dizelskim gorivom. Usporedna analiza

In the present article, two models based on the artificial neural network methodology (ANN) have been optimised to predict the density (ρ) and kinematic viscosity (μ) of different systems of biofuels and their blends with diesel fuel. An experimental database of 1025 points, including 34 systems (15 pure systems, 14 binary systems, and 5 ternary systems) was used for the development of these models. These models use six inputs, which are temperature (T) in the range of −10 – 200 °C, volume fractions (X1, X2, X3) in the range of 0–1, and to distinguish these systems, we used kinematic viscosity at 20 °C in the range of 0.67–74.19 mm2 s–1 and density at 20 °C in the range of 0.7560–0.9188 g cm–3. The best results were obtained with the architecture of {6-26-2: 6 neurons in the input layer – 26 neurons in the hidden layer – 2 neurons in the output layer}. Results of comparison between experimental and simulated values in terms of the correlation coefficients were: R2 = 0.9965 for density, and R2 = 0.9938 for kinematic viscosity. A 238 new database experimental of 4 systems (2 pure systems, 1 binary system, and 1 ternary system) was used to check the accuracy of the two ANN models previously developed. Results of prediction performances in terms of the correlation coefficients were: R2 = 0.9980 for density, and R2 = 0.9653 for kinematic viscosity. Comparison of validation results with those of the other studies shows that the neural network models gave far better results. This work is licensed under a Creative Commons Attribution 4.0 International License.U ovom članku dva modela zasnovana na metodologiji umjetne neuronske mreže (ANN) optimizirana su za predviđanje gustoće (ρ) i kinematičke viskoznosti (μ) različitih sustava biogoriva i njihovih mješavina s dizelskim gorivom. Za razvoj tih modela upotrijebljena je eksperimentalna baza podataka od 1025 točaka, uključujući 34 sustava (15 čistih sustava, 14 binarnih sustava i 5 ternarnih sustava). Ti modeli koriste šest ulaza: temperatura (T) u rasponu od −10 do 200 °C, volumni udjeli (X1, X2, X3) u rasponu 0 – 1, a za razlikovanje tih sustava korištena je kinematička viskoznost pri 20 °C u rasponu 0,67 – 74,19 mm2 s–1 i gustoća pri 20 °C u rasponu 0,7560 – 0,9188 g cm–3. Najbolji rezultati dobiveni su arhitekturom {6-26-2: 6 neurona u ulaznom sloju – 26 neurona u skrivenom sloju – 2 neurona u izlaznom sloju}. Rezultati usporedbe eksperimentalnih i simuliranih vrijednosti u smislu korelacijskih koeficijenata bili su: R2 = 0,9965 za gustoću i R2 = 0,9938 za kinematičku viskoznost. Za provjeru točnosti dva prethodno razvijena modela ANN upotrijebljeno je 238 novih eksperimentalnih baza podataka s 4 sustava (2 čista sustava, 1 binarni sustav i 1 ternarni sustav). Rezultati performansi predviđanja s obzirom na korelacijske koeficijente bili su: R2 = 0,9980 za gustoću i R2 = 0,9653 za kinematičku viskoznost. Usporedba rezultata validacije s rezultatima drugih studija pokazuje da su modeli neuronske mreže dali znatno bolje rezultate. Ovo djelo je dano na korištenje pod licencom Creative Commons Imenovanje 4.0 međunarodna

Academic advisory needs for university students and suggestions for organizing them

في ظل ظهور الكثير  من التغيرات الأسرية والاجتماعية والتقدم العلمي والتكنولوجي، وما نتج عنه من تطوّر في التعليم و في مسار العمل، بالإضافة إلى التغيرات التي تشهدها المراحل العمرية( الانتقالية) التي يعيشها الفرد. ظهرت أهمية تقييم الحاجات الإرشادية كخطوة أولية وأساسية في تقديم الخدمات الإرشادية، حيث اصبح الإرشاد أمراً حتمياً، خاصة اذا تعلّق الأمر بالطلبة الجامعيين الذين لديهم حاجات إرشادية أكاديمية، اضافة الى حاجاتهم المرتبطة بجوانب حياتهم المختلفة، لذا سنهتم في هذه الدراسة بالحاجات الارشادية للطلبة الجامعيين و أهميتها في مسارهم الأكاديمي و نتطرق الى أهدافها للوصول الى بعض الاقتراحات التي من شأنها تحسين العملية الارشادية الاكاديمية.In the light of the emergence of family and social changes and scientific and technological development, which have led to development in the field of education and work, in addition to the changes in the stages of life (transition) experienced by the individual. The importance of the assessment of counseling needs emerged as an essential step in the presentation of counseling services. When it became necessary, especially if it was to concede to university students who have counseling academic needs, in addition to their needs related to their different areas of life. In this study, we focused on the comforting needs of university students and their importance in their careers. We discuss their goals to come up with some suggestions for improving the academic counseling process

A comprehensive analysis of 3' end sequencing data sets reveals novel polyadenylation signals and the repressive role of heterogeneous ribonucleoprotein C on cleavage and polyadenylation

Alternative polyadenylation (APA) is a general mechanism of transcript diversification in mammals, which has been recently linked to proliferative states and cancer. Different 3' untranslated region (3' UTR) isoforms interact with different RNA-binding proteins (RBPs), which modify the stability, translation, and subcellular localization of the corresponding transcripts. Although the heterogeneity of pre-mRNA 3' end processing has been established with high-throughput approaches, the mechanisms that underlie systematic changes in 3' UTR lengths remain to be characterized. Through a uniform analysis of a large number of 3' end sequencing data sets, we have uncovered 18 signals, six of which are novel, whose positioning with respect to pre-mRNA cleavage sites indicates a role in pre-mRNA 3' end processing in both mouse and human. With 3' end sequencing we have demonstrated that the heterogeneous ribonucleoprotein C (HNRNPC), which binds the poly(U) motif whose frequency also peaks in the vicinity of polyadenylation (poly(A)) sites, has a genome-wide effect on poly(A) site usage. HNRNPC-regulated 3' UTRs are enriched in ELAV-like RBP 1 (ELAVL1) binding sites and include those of the CD47 gene, which participate in the recently discovered mechanism of 3' UTR-dependent protein localization (UDPL). Our study thus establishes an up-to-date, high-confidence catalog of 3' end processing sites and poly(A) signals, and it uncovers an important role of HNRNPC in regulating 3' end processing. It further suggests that U-rich elements mediate interactions with multiple RBPs that regulate different stages in a transcript's life cycle

Plasmacytoid dendritic cells contribute to vascular endothelial dysfunction in type 2 diabetes

ObjectiveType 2 diabetes (T2D) is associated with an increased risk of cardiovascular disease due to macro- and microvascular dysfunction. This study aimed to investigate the potential involvement of plasmacytoid dendritic cells (pDCs) in T2D-related vascular dysfunction.Approach and resultspDCs were isolated from db/db and control mice. It was found that pDCs from db/db mice impaired endothelial cell eNOS phosphorylation in response to ATP and decreased vascular endothelium-dependent relaxation compared to pDCs from control mice. Moreover, isolated CD4+ cells from control mice, when stimulated overnight with high glucose and lipids, and isolated pDCs from db/db mice, display elevated levels of ER stress, inflammation, and apoptosis markers. Flow cytometry revealed that pDC frequency was higher in db/db mice than in controls. In vivo, the reduction of pDCs using anti-PDCA-1 antibodies in male and female db/db mice for 4 weeks significantly improved vascular endothelial function and eNOS phosphorylation.ConclusionpDCs may contribute to vascular dysfunction in T2D by impairing endothelial cell function. Targeting pDCs with anti-PDCA-1 antibodies may represent a promising therapeutic strategy for improving vascular endothelial function in T2D patients. This study provides new insights into the pathogenesis of T2D-related vascular dysfunction and highlights the potential of immunomodulatory therapies for treating this complication. Further studies are warranted to explore the clinical potential of this approach