Hybrid Topology Research Articles

FRDS: An efficient unique on-Chip interconnection network architecture

Networks-on-Chip (NoC) is an impending research area for designing future System-on-Chip (SoC). NoC futures are allied with intellectual property (IP) reusability, parallel communication within IPs and scalability against standard interconnection NoC topology. In this paper, we introduce a new hybrid topology namely Four Regular Dense Spidergon (FRDS) based deterministic NoC architecture with 64 cores. We propose cluster and generic heuristic based approach For mapping of applications onto FRDS topology. Genetic algorithm (GA) ＋ simulated annealing (SA) have been considered under generic heuristic approach for successful mapping of core into topology and fair comparison of the performance of the proposed FRDS. Under normalized condition with respect to Mesh, experimental findings of proposed FRDS against real benchmark traces provide an average improvement on execution time with 1.20% and 4.81% over DMesh and ZMesh. Further, an average improvement on energy consumption was obtained 8.13% and 5.35% over DMesh and ZMesh. We adopt constant geometric traffic and the synthetic traffic pattern to measure the performance of proposed FRDS. The experimental results clearly indicates an improvement in power latency product under geometric traffic by 16.27% and 12.23% over DMesh and ZMesh. Similarly under synthetic traffic pattern, the proposed FRDS offers an improvement up to 22.51% and 45.53% over DMesh and ZMesh respectively. To realize the effectiveness of the link usage, brief evaluation of link utilization has been carried out with balanced load.

Redox flow battery time‐varying parameter estimation based on high‐order sliding mode differentiators

A new insight into vanadium redox flow batteries (VRFB) parameter estimation is presented. Driven by the electric vehicles proliferation, a hybrid fast-charging station with grid and a renewable energy connection is particularly considered. In this stationary application, the VRFB is operating as buffering module. This hybrid topology could contribute to reduce the grid connection cost of the charging station. However, to make VRFB a viable technology, improvements are needed. Among these, some of the most important are in the field of the estimation of the battery's State of Charge, State of Health, and internal parameters. The proposed estimation method is based on a recursive least square (RLS) estimation algorithm with forgetting factor, combined with a sliding mode finite-time convergent differentiation algorithm. The latter provides robust exact derivatives of both VRFB's current and voltage with a high degree of noise rejection, required by the RLS algorithm to perform a precise estimation. The proposed sliding mode-based estimation setup is completed with a systematic methodology to guarantee the validity of the on-line estimated values, depending on the persistence of excitation of the measured current and voltage. Finally, the methodology is thoroughly analysed and validated by computer simulation.

A 13-Bit ENOB Third-Order Noise-Shaping SAR ADC Employing Hybrid Error Control Structure and LMS-Based Foreground Digital Calibration

This article presents a third-order noise-shaping (NS) successive approximation register (SAR) analog-to-digital converter (ADC), which exploits a hybrid error control topology to increase the order of the noise-transfer function (NTF). This scheme is a hybrid of two NS stages, namely, a cascaded integrator feed-forward (CIFF) and an error feedback (EF). This EF-CIFF structure contributes a more effective NS capability and enhances the robustness of the high-order NTF. An improved dither-based digital calibration is developed to mitigate the harmonic distortion caused by the capacitor mismatch. Due to the usage of an averaging filter, this calibration greatly reduces the interference of quantization noise on mismatch extraction while only needing a minimum modification in a standard SAR Topology. Hence, our scheme is simple and inherently robust to the process, voltage, and temperature variation. Based on an 8-bit SAR, our prototype is fabricated in a 130-nm CMOS process. It consumes a 96- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{W}$ </tex-math></inline-formula> power when operating at a 2-MS/s sampling frequency with a 1.2-V supply. The proposed NS-SAR yields a peak Schreier figure of merit of 170.7 dB with a signal-to-noise-and-distortion ratio (SNDR) of 79.57 dB at an oversampling ratio of 8.

A very high-resolution refractive index sensor based on hybrid topology of photonic crystal cavity and plasmonic nested split-ring resonator

In this paper, an optical refractive index (RI) sensor based on a photonic crystal and plasmonic (PhC-P) hybrid topology is designed. The sensor's structure is composed of nested circular metallic split-ring resonators (NCMSRR), which are embedded inside a hexagonal cavity in a rod-type photonic crystal (PhC) structure. The finite-difference time-domain (FDTD) method is used for the numerical simulation of the sensor. The obtained results show that by the cooperative coupling between the surface plasmon polaritons (SPP) induced by the NCMSRR and resonant PhC cavity modes, a hybrid PhC-P mode is created. The hybrid mode provides unique opportunities, not only for incrementing the sensitivity but also for obtaining a much higher figure of merit (FoM) compared to modes belonging to purely plasmonic or purely PhC sensors. The simulation results demonstrate a fairly high sensitivity of 1250 nm/RIU and an excellent FoM of 2083 RIU−1 when the proposed sensor is exposed to hazardous gases. These results show considerable improvement compared to the works published in the literature. Accordingly, the sensor proposed in this paper has tremendous potential to be used for high-sensitivity and high-resolution sensing applications at optical communication wavelengths.

Temporal-spatial scheduling of electric vehicles in AC/DC distribution networks

With the rapid development of power electronic technology, the AC/DC hybrid distribution network has become a new trend of distribution system architectures in recent years. And meanwhile, electric vehicles (EVs) equipped with both AC and DC charging interfaces tend to be utilized as ideally dispatchable resources in not only temporal but also spatial dimensions, whose charging/discharging schemes remarkably impact the secure and economical operation of distribution networks. In view of this background, this paper proposes a temporal-spatial scheduling model of EVs in AC/DC distribution networks, targeting at the optimum of the whole network losses as well as the inconveniences of EV users originated from following scheduling instructions. Besides the traditional constraints relevant to EVs’ temporal scheduling in just-AC distribution networks, the AC/DC hybrid topology and the restrictions for EVs’ spatial scheduling are properly involved in the proposed model. After a reasonable simplification procedure, the proposed model is represented as a Mixed Integer Quadratic Program (MIQP) problem that can be efficiently solved by off-the-shelf optimization algorithms. Through the analyses of a coupled electrical-geographical AC/DC distribution network, the proposed model can bring 6.3% and 6.8% cost savings respectively on two typical days.

Review and design of modular multilevel inverter with modified multicarrier PWM techniques for solar PV applications

PurposeThese implementations not only generate excessive voltage levels to enhance the quality of power but also include a detailed investigating of the various modulation methods and control schemes for multilevel inverter (MLI) topologies. Reduced harmonic modulation technology is used to produce 11-level output voltage with the production of renewable energy applications. The simulation is done in the MATLAB/Simulink for 11-level symmetric MLI and is correlated with the conventional inverter design.Design/methodology/approachThis paper is focused on investigating the different types of asymmetric, symmetric and hybrid topologies and control methods used for the modular multilevel inverter (MMI) operation. Classical MLI configurations are affected by performance issues such as poor power quality, uneconomic structure and low efficiency.FindingsThe variations in both carrier and reference signals and their performance are analyzed for the proposed inverter topologies. The simulation result compares unipolar and bipolar pulse-width modulation (PWM) techniques with total harmonic distortion (THD) results. The solar-fed 11-level MMI is controlled using various modulation strategies, which are connected to marine emergency lighting loads. Various modulation techniques are used to control the solar-fed 11-level MMI, which is connected to marine emergency lighting loads. The entire hardware system is controlled by using SPARTAN 3A field programmable gate array (FPGA) board and the least harmonics are obtained by improving the power quality.Originality/valueThe simulation result compares unipolar and bipolar PWM techniques with THD results. Various modulation techniques are used to control the solar-fed 11-level MMI, which is connected to marine emergency lighting loads. The entire hardware system is controlled by a SPARTAN 3A field programmable gate array (FPGA) board, and the power quality is improved to achieve the lowest harmonics possible.

Integrated Sensing Devices for Disease Prevention and Health Alerts in Smart Homes.

The rapid development of elderly population is changing demographics in Europe and North America and imposes barriers to healthcare systems that may reduce the quality of service. Telemedicine is a potential solution supporting the real-time and remote monitoring of subjects as well as bidirectional communication with medical personnel for care delivery at the point of perception. Smart homes are private spaces where young or elderly, healthy or diseased-suffering, or disabled individuals spend the majority of their time. Hence, turning smart homes into diagnostic spaces for continuous, real-time, and unobtrusive health monitoring allows disease prediction and prevention before the subject perceives any symptoms. According to the World Health Organization, health, well-being, and quality of life assessment require the monitoring of interwoven domains such as environmental, behavioral, physiological, and psychological. In this work, we give an overview on sensing devices and technologies utilized in smart homes, which can turn the home into a diagnostic space. We consider the integration of sensing devices from all four WHO domains with respect to raw and processed data, transmission, and synchronization. We apply the bus-based scalable intelligent system to construct a hybrid topology for hierarchical multi-layer data fusion. This enables event detection and alerting for short-time as well as prediction and prevention for long-time monitoring.

Toward 2030 CO2 targets – high efficiency engine with gasoline compression ignition technology on a hybrid electric vehicle simulation

The pressure to reduce CO2 and pollutants of internal combustion engine (ICE) powered vehicles is higher than ever. The existing gasoline and diesel engine vehicles face a critical challenge to adjust to these stringent demands. By combining a gasoline like clean fuel with a high efficiency thermodynamic cycle (compression ignition), it is possible to create a powertrain that is clean, both globally and locally, and so breaking the historical trade-off between decreasing CO2 versus pollutants. However, very low vehicle out CO2 cannot be achieved if ICEs are not combined with a hybrid electric powertrain. In this paper, the potential of the gasoline like fuel in compression ignition (GCI) vehicle in combination with hybridization is assessed. Three different hybrid topologies have been theoretically assessed in a first step. Afterwards, the most promising has been deeply analyzed by means of longitudinal vehicle simulation. Here, the corresponding hybrid control strategy is optimized. The battery size has been adjusted as well targeting the optimum capacity when using a HEV instead of a PHEV. The combination of highly efficient GCI engine in combination with such an optimized hybrid topology represents an extreme value regarding CO2 reduction for passenger cars. Such vehicles could contribute largely to the emission targets set for 2030 by the European Commission. In summary, this paper presents engineering solution to comply with future greenhouse gas regulations through advanced engine technology and HEV technology.

Ресурсонезависимое описание информационных графов с дистрибутивными операциями на языке программирования Set@l

In the paper, we suggest to transform a standard sequential topology of an information graph with distributive operations into its hybrid version with sequential and parallel fragments. Such transformation allows to provide efficient description of calculations in the resource-independent form. The result topology depends on available hardware resource of a reconfigurable system and provides an increase in the special performance in comparison to the initial topology. We have developed an algorithm of a linear structure transformation into various hybrid topologies according to the configuration of the computing system. The algorithm is described in the Set@l programming language.

Comparative Evaluation of the Two Multilevel Concepts With Full ZVS Operation Employing WBG Devices for Use in 1500-V PV Systems

A multi-level boost topology based on a flying capacitor is compared in this work with the hybrid, multi-level, partial power processing topology already presented in the literature for use as a highly efficient and compact dc/dc stage in 1500-V, two-stage, grid-connected PV systems. Different variations of the resonant stage of the hybrid topology are analyzed and compared in terms of losses, volume and complexity. Full multivariable optimization is conducted for the multi-level boost topology with different number of levels and for all the analyzed variations of the resonant stage of the hybrid topology. Appropriately rated new classes of 650-V and 900-V WBG devices are included in the optimization algorithm. It is concluded that due to the dominant conduction losses and gap in the voltage rating of the commercially available WBG devices between 650V and 200V, increase of the number of levels over 4 leads to the deteriorated loss and volume performances. All the analysis related to the resonant stage of the hybrid topology is confirmed by detailed and comprehensive measurements of two prototypes of 4kW of nominal and 7kW of maximal power. Additionally, all the loss models applied in the optimization algorithms presented in this paper are confirmed by detailed measurements, thermal calibration and finite element thermal simulations of the wide bandgap devices and inductor designs employed in this work.

Computer Network Topologies

Abstract: Network topologies is various components of network link nodes, link, peripherals are arranged. The way of connecting the computers is called as the topology.so depending on the manner of connecting the computers we can have different network topologies. Network topology is links and nodes of a network are arranged to related are arranged to each other. They describe the physical and logical arrangement of network nodes. The way in which different system and node are connect and communicate with each other is determined by topology of the network. Keywords: Star Topology, Bus Topology, Ring Topology, Hybrid Topology, Mesh Topology, Tree Topology

Quantum Cooperative Multicast in a Quantum Hybrid Topology Network

Quantum multicast is a significant transmission mode in a multiparty communication scenario. Multisource collaboration can further enhance the efficient multicast. However, it remains a challenge to realize quantum multicast with a cooperative way in a complex topology network. In this article, we propose a scheme of quantum cooperative multicast in a hybrid topology network. It provides information aggregation and simultaneous multipoint transmission services. First, collaborative information aggregation allows central network data to be integrated into the aggregation node. By exploiting the quantum multicast mode, the aggregation node can simultaneously deliver integrated quantum states to multiple targets. Second, our scheme is feasible for dynamic network expansion. It is capable of extending the network architecture iteratively, while the peer network requests can be handled in parallel. Finally, the new scheme shows great application potential in the distributed quantum network. It is a promising candidate for the implementation of quantum data disaster backup in future.

Merging slime mould with whale optimization algorithm for optimal allocation of hybrid power flow controller in power system

ABSTRACT This manuscript proposes the optimal allocation of hybrid power flow controller (HPFC) using hybrid technique. The proposed technique is the implementation of Integrated Slime Mould Algorithm (ISMA). The searching behaviour of Slime Mould Algorithm (SMA) is enhanced by the position updating behaviour of the whale optimisation algorithm (WOA). HPFC, a hybrid topology, has VAR compensator or an impedance-type FACTS device, most probably obtainable at power system, and two voltage source converters depend on controllers share a general DC link. The novel contributions of allocating HPFC at optimal location for multi-objective fitness functions denote minimal real power loss of system as well as minimal generation cost using ISMA method. Here, ISMA method optimises maximum line of power loss as appropriate location of unified power flow controller (UPFC). The optimal location parameters and dynamic stability restrictions are restored with normal constraints, employing UPFC optimal capacity has been optimised to decreased cost with the help of ISMA technique.

Rapid label-free colorimetric dual-functional aptasensor for β-lactoglobulin detection based on a rational tailoring strategy

β-lactoglobulin (β-LG) is a nonnegligible allergenic protein found in cow milk. A label-free, enzyme-free, dual-functional aptameric sensor was constructed based on rational aptamer tailoring for β-LG detection. Via an established three-step rational tailoring strategy, the original aptamer was transformed from an inflexible antiparallel topology into the flexible, antiparallel/parallel hybrid topology, enlg2-pl3. enlg2-pl3 displayed the dual-functionality of not only binding with β-LG via the antiparallel conformation but also outputting signals via the parallel type. The dual-functionality depended on the conformational conversion of enlg2-pl3. The β-LG-driven conformational conversion to antiparallel type was the detection basis of aptasensor. The detection conditions were optimized regarding ions, hemin, chromogenic substrate, pH levels, and detection time. Furthermore, the aptasensor offered advantages, such as cost-efficiency, simple operation, 40 min rapid detection, excellent specificity, and a sensitivity of a three-orders of magnitude linear range and an 8.23-fold linear curve slope, meeting the point-of-care testing (POCT) requirements for dairy analysis.

A Formation Control Method for AUV Group Under Communication Delay.

This article presents a consistency control algorithm for the autonomous underwater vehicle (AUV) group combined with the leader–follower approach under communication delay. First, the six-degree-of-freedom (DoF) model of AUV is represented, and the graph theory is used to describe the communication topology of the AUV group. Especially, a hybrid communication topology is introduced to adapt to large formation control. Second, the distributed control law is constructed by combining the consensus theory with the leader–follower method. The consistency control algorithms for homogeneous and heterogeneous AUV groups based on the leader–follower approach under communication delay are proposed. Stability criteria are established to guarantee the consensus based on the Gershgorin disk theorem and Nyquist law, respectively. Finally, numerous simulation experiments are carried out to show the effectiveness and superiority of the proposed algorithms.

Intelligent model for active power prediction of a small wind turbine

Abstract In this study, a hybrid model based on intelligent techniques is developed to predict the active power generated in a bioclimatic house by a low power wind turbine. Contrary to other researches that predict the generated power taking into account the speed and the direction of the wind, the model developed in this paper only uses the speed of the wind, measured mainly in a weather station from the government meteorological agency (MeteoGalicia). The wind speed is measured at different heights, against the usual measurements in others researches, which uses the wind speed and the direction measured in a weather station on the wind turbine nacelle. The prediction is performed 30 minutes ahead, what ensures that the Building Management System knows the energy generated by the low power wind turbine 30 minutes before, and it can adapt the consumption of different equipment in the house to optimize the power use. The main objective is to allow the Building Management System to optimize the uses of energy, taking into account the predicted amount of energy that will be produced and the energy consumed in the house. The developed model uses a hybrid topology with four clusters to improve the prediction, achieving an error lower than 6.5% for Mean Absolute Error measured in a final test. To perform this test, part of the original dataset was isolated from the beginning of the training process to check the model with a dataset that is not used before, simulating the model as it is receiving new data.

Unified Mode-Based Description of Arbitrary Hybrid and Electric Powertrain Topologies

To find the optimal powertrain design for hybrid and electric vehicles in terms of energy efficiency and performance, automatised optimisation tools are often applied. These require a mathematical model of the powertrain configuration, which is usually done on the level of components, such as planetary gear sets (PGSs), clutches and brakes. This, however, leads to a huge design space with lots of functional redundancy. In fact, each functional powertrain mode can be realised by various component combinations. In this paper, a novel mode-based modelling technique for arbitrary hybrid and electric powertrain configurations with up to one internal combustion engine (ICE) and two electrical machines (EMs) is proposed. This allows to easily analyse multi-mode hybrid and electric powertrains on a purely functional basis. Additionally, it reduces mode describing parameters to the minimum amount required. First, an existing graphical representation of hybrid powertrains with one ICE and one EM is analysed and formalised. Based on that, virtual powertrain nodes are defined. These are used to compose all hybrid and electric powertrain modes. Five of them are presented in detail and plotted within a three-dimensional ratio plot. Using a first case study, it is shown how the ratio plot can be used to analyse arbitrary multi-mode powertrains. Within a second case study, it is demonstrated how optimal parameter sets for single-mode powertrain configurations can be identified using the derived model.

Current Stress Optimization for Double-Sided CLLLC Topology-Based IPT System With Constant Output Current Tolerating Pad Misalignments

In the inductive power transfer (IPT) system, a hybrid topology with the anti-misalignment ability and load-independent output is usually used to improve the stability of the system and simplify the control scheme. However, the power distribution of the hybrid topology is uneven with misalignment, resulting in high current stresses in partial coils. In order to minimize the current stresses, a parameter design method with double-sided capacitor-inductor-inductor-inductor-capacitor compensation topology is proposed to optimize the coil currents without the effect on the output fluctuation. Finally, a 3.5-kW laboratory-scale prototype was built to validate the proposed method. The results show that the proposed parameter design method can minimize the maximum current stress significantly, and the hybrid IPT system has good performances of misalignment tolerance and load-independent output current.

Reducing the fuel consumption of light aircraft

Given that significant increases have been made in the gravimetric specific power of permanent magnet synchronous machines, we reassess the effect that parallel, series and power/split hybrid topologies have on reducing the fuel consumption of light aircraft. Given the difficulties in preventing the weight of a hybrid-powered aircraft from exceeding the weight of the retrofitted conventionally powered aircraft, an analysis is conducted to assess the effects of weight increase over powertrain efficiency increase on fuel consumption. Finally, we examine two new combustion technologies to assess their potential for reducing fuel consumption and their practicality for light aircraft.

A Grey Wolf Optimized 15-Level Inverter Design with Confined Switching Components

Multilevel inverters are a new class of dc-ac converters designed for high-power medium voltage and power applications as they work at high switching frequencies and in renewable applications by avoiding stresses like dv/dt and has low harmonic distortion in their output voltage. In variable speed drives and power generation systems, the use of multilevel inverters is obligatory. To estimate the switching positions in inverter configuration with low harmonic distortion value, a fast sequential optimization algorithm has been established. For harmonic reduction in multilevel inverter design, a hybrid optimization technique combining Firefly and the Genetic algorithm was used. In several real-time systems and for solving complex engineering problems, optimization approaches are gaining popularity. Based on Grey Wolf Optimization (GWO), this research paper proposes a novel multilevel inverter architecture. The GWO algorithm is based on the natural leadership hierarchy and hunting mechanism of grey wolves (Canis lupus). The Grey Wolf Optimizer (GWO) algorithm is used to find the best switching angles for a cascaded multilevel inverter in order to eliminate some high order harmonics while sustaining the desired fundamental voltage. The proposed inverter has 15 stages, and the circuit’s unique feature includes a limited switching device. This proposed method comprises, MOSFET-based switches well as three DC sources in the main circuit. The switching parameters of the inverter topology are tuned using GWO in this methodology. The THD value of the proposed system is reduced to 6.629% compared to that of Multilevel Inverter using Genetic Algorithm, standalone power supply, Firefly assisted Genetic Algorithm, hybrid APSO algorithm, DC voltage regulation and FPGA. A few simulation studies have been included in this paper to affirm the capability of the hybrid topologies with various condition parameters, dynamic changes, and modulation indexes.